Home Alphabetical Year Application Task Annotation
2018-present 2014-2017 Before-2013
- Summary: A dataset of pedestrians with 346 video sequences showing pedestrians at the time of crossing in different geographical locations and under different weather conditions
- Applications: Video prediction, Action prediction, Trajectory prediction, Other prediction
- Data type and annotations: RGB, bounding box, attribute, temporal segment, Tracking ID
- Task: Driving
- Summary: A dataset of 620 video sequences of traffic accidents recorded in six cities
- Applications: Action prediction
- Data type and annotations: RGB, bounding box, object class, temporal segment, Tracking ID
- Task: Driving
- Summary: A dataset of 3 surgical operation actions performed by 8 subjects using robotic arms
- Applications: Action prediction
- Data type and annotations: RGBD, Activity Label, Temporal Segment
- Task: Robot
- Summary: A dataset of 220+ K videos of different actors interacting with various objects
- Applications: Video prediction
- Data type and annotations: RGB, Activity Label
- Task: Object interaction
- Summary: A large-scale dataset 300K+ video clips of 400 human action classes, e.g. drawing, drinking, laughing, each containing ~10s clips
- Applications: Other prediction
- Data type and annotations: RGB, activity label
- Task: Activity
- Summary: A dataset of simulated dynamic objects.
- Applications: Trajectory prediction
- Data type and annotations: Trajectory
- Task: Simulation
- Summary: A dataset of fishes and mice in a lab environment with corresponding 2D poses
- Applications: Motion prediction
- Data type and annotations: Depth, 3D pose
- Task: Animal
- Summary: A dataset containing 100 repetitions of a consistent route through Oxford driving by a vehicle under different weather and traffic conditions
- Applications: Trajectory prediction
- Data type and annotations: Stereo RGB, LIDAR, vehicle sensors
- Task: Driving
- Summary: A multimodal dataset of 41 daily activities and 10 interaction actions recorded from 3 camera views using 60 subjects
- Applications: Action prediction
- Data type and annotations: RGBD, IR, 3D pose, multiview, temporal segment
- Task: Activity, Interaction
- Summary: A dataset of 1M+ cooking recipes with 13M food images
- Applications: Action prediction
- Data type and annotations: RGB, text
- Task: Cooking
- Summary: A dataset of 28K indoor LIDAR scans showing the surroundings of a mobile robot in stationary or moving states
- Applications: Trajectory prediction
- Data type and annotations: LIDAR, 3D bounding box, attribute
- Task: Driving
- Summary: A risk-assessment dataset of failed activity videos with 3K samples annotated at every 15 frames with bounding boxes around risky regions
- Applications: Action prediction
- Data type and annotations: RGB, bounding box, trajectory, temporal segment
- Task: Risk assessment
- Summary: A subset of Cityscapes dataset with fine-grained annotations for pedestrians and vehicles in additional 20K images with a total of 35K+ bounding boxes for pedestrians
- Applications: Trajectory prediction
- Data type and annotations: Stereo RGB, bounding box, semantic segment
- Task: Driving
- Summary: An RGBD dataset of objects with corresponding 3D bounding boxes collected using a mobile robot
- Applications: Trajectory prediction
- Data type and annotations: RGBD, 3D bounding box
- Task: Driving
- Summary: A dataset of street-level images with the corresponding instance and semantic segmentation
- Applications: Trajectory prediction
- Data type and annotations: RGB, Bounding Box, Semantic Segment
- Task: Driving
- Summary: A dataset of photo realistic 194K+ RGBD images of 90 indoor environments
- Applications: Other prediction
- Data type and annotations: RGBD, Semantic Segment
- Task: Simulation
- Summary: A dataset of 100K driving sequences with annotations fo 10 traffic objects annotated at 10Hz
- Applications: Video prediction
- Data type and annotations: RGB, Bounding Box, Semantic Segment, Lane Marking, Drivable Areas
- Task: Driving
- Summary: A dataset of 220K+ videos of 174 different activities
- Applications: Video prediction
- Data type and annotations: RGB, Activity Label
- Task: Activity
- Summary: A dataset of 3D poses recorded over time (3D) at 60 fps
- Applications: Motion prediction
- Data type and annotations: 3D Pose
- Task: Activity
- Summary: A dataset consisting of 150 video sequences with over 10K frames and 376 objects with associated segmentation masks.
- Applications: Video prediction
- Data type and annotations: RGB, Segmentation
- Task: Activity
- Summary: A dataset of action images with 23K+ images and 101 activity classes collected from existing action video datasets
- Applications: Action prediction
- Data type and annotations: RGB, activity label
- Task: Activity
Joint Attention in Autonomous Driving (JAAD) link paper
Used in papers
Chaabane et al., "Looking Ahead: Anticipating Pedestrians Crossing with Future Frames Prediction", WACV, 2020. paper arxiv
Gujjar et al., "Classifying Pedestrian Actions In Advance Using Predicted Video Of Urban Driving Scenes", ICRA, 2019. paper
Rasouli et al., "PedFormer: Pedestrian Behavior Prediction via Cross-Modal Attention Modulation and Gated Multitask Learning", ICRA, 2023. paper arxiv
Song et al., "Pedestrian Intention Prediction Based on Traffic-Aware Scene Graph Model", IROS, 2022. paper
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Datasets
Metrics
Bibtex
@InProceedings{Song_2022_IROS,
author = "Song, Xingchen and Kang, Miao and Zhou, Sanping and Wang, Jianji and Mao, Yishu and Zheng, Nanning",
booktitle = "IROS",
title = "Pedestrian Intention Prediction Based on Traffic-Aware Scene Graph Model",
year = "2022"
}
Zhai et al., "Social Aware Multi-Modal Pedestrian Crossing Behavior Prediction", ACCV, 2022. paper code
Rasouli et al., "Bifold and Semantic Reasoning for Pedestrian Behavior Prediction", ICCV, 2021. paper arxiv
Sui et al., "Joint Intention and Trajectory Prediction Based on Transformer", IROS, 2021. paper
Liu et al., "Spatiotemporal Relationship Reasoning for Pedestrian Intent Prediction", RAL, 2020. paper arxiv
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Datasets
Metrics
Bibtex
@Article{Liu_2020_RAL,
author = "Liu, B. and Adeli, E. and Cao, Z. and Lee, K. and Shenoi, A. and Gaidon, A. and Niebles, J. C.",
journal = "RAL",
title = "Spatiotemporal Relationship Reasoning for Pedestrian Intent Prediction",
year = "2020",
volume = "5",
number = "2",
pages = "3485-3492"
}
Saleh et al., "Real-Time Intent Prediction Of Pedestrians For Autonomous Ground Vehicles Via Spatio-Temporal DenseNet", ICRA, 2019. paper arxiv
Aliakbarian et al., "VIENA2: A Driving Anticipation Dataset", ACCV, 2018. paper arxiv
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Datasets
Metrics
Bibtex
@InProceedings{Aliakbarian_2018_ACCV,
author = "Aliakbarian, Mohammad Sadegh and Saleh, Fatemeh Sadat and Salzmann, Mathieu and Fernando, Basura and Petersson, Lars and Andersson, Lars",
editor = "Jawahar, C. V. and Li, Hongdong and Mori, Greg and Schindler, Konrad",
title = "{VIENA2}: A Driving Anticipation Dataset",
booktitle = "ACCV",
year = "2018"
}
Rasouli et al., "Are They Going To Cross? A Benchmark Dataset And Baseline For Pedestrian Crosswalk Behavior", ICCVW, 2017. paper
Rasouli, "A Novel Benchmarking Paradigm and a Scale- and Motion-Aware Model for Egocentric Pedestrian Trajectory Prediction", ICRA, 2024. paper arxiv code
Feng et al., "Multimodal Forward Generation Transformer Network for Inconspicuous Pedestrian Trajectory Prediction", RAL, 2024. paper
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Datasets
Metrics
Bibtex
@ARTICLE{Feng_Multimodal_2024_RAL,
author = "Feng, Ang and Qiu, Ruiqi and Wang, Jinglong and Gong, Jun and Yi, Yang and Dong, Mingtao",
journal = "RAL",
title = "Multimodal Forward Generation Transformer Network for Inconspicuous Pedestrian Trajectory Prediction",
year = "2024",
volume = "9",
number = "3",
pages = "2224-2231"
}
Huynh et al., "Online Adaptive Temporal Memory With Certainty Estimation for Human Trajectory Prediction", WACV, 2023. paper
Halawa et al., "Action-Based Contrastive Learning for Trajectory Prediction", ECCV, 2022. paper arxiv
Wang et al., "Stepwise Goal-Driven Networks for Trajectory Prediction", RAL, 2022. paper arxiv code
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Datasets
Metrics
Bibtex
@Article{Wang_2022_RAL_2,
author = "Wang, Chuhua and Wang, Yuchen and Xu, Mingze and Crandall, David J.",
journal = "RAL",
title = "Stepwise Goal-Driven Networks for Trajectory Prediction",
year = "2022",
volume = "7",
number = "2",
pages = "2716-2723"
}
Neumann et al., "Pedestrian and Ego-Vehicle Trajectory Prediction From Monocular Camera", CVPR, 2021. paper code
Yao et al., "BiTraP: Bi-Directional Pedestrian Trajectory Prediction With Multi-Modal Goal Estimation", RAL, 2021. paper arxiv code
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Datasets
Metrics
Bibtex
@Article{Yao_2021_RAL,
author = "Yao, Yu and Atkins, Ella and Johnson-Roberson, Matthew and Vasudevan, Ram and Du, Xiaoxiao",
journal = "RAL",
title = "{BiTraP}: Bi-Directional Pedestrian Trajectory Prediction With Multi-Modal Goal Estimation",
year = "2021",
volume = "6",
number = "2",
pages = "3459-3466"
}
Mangalam et al., "Disentangling Human Dynamics for Pedestrian Locomotion Forecasting with Noisy Supervision", WACV, 2020. paper arxiv
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Datasets
Metrics
Bibtex
@InProceedings{Mangalam_2020_WACV,
author = "Mangalam, Karttikeya and Adeli, Ehsan and Lee, Kuan-Hui and Gaidon, Adrien and Niebles, Juan Carlos",
title = "Disentangling Human Dynamics for Pedestrian Locomotion Forecasting with Noisy Supervision",
booktitle = "WACV",
year = "2020"
}
Ansari et al., "Simple means Faster: Real-Time Human Motion Forecasting in Monocular First Person Videos on CPU", IROS, 2020. paper arxiv
Rasouli et al., "PIE: A Large-Scale Dataset And Models For Pedestrian Intention Estimation And Trajectory Prediction", ICCV, 2019. paper code
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Datasets
Metrics
Bibtex
@InProceedings{Rasouli_2019_ICCV,
author = "Rasouli, Amir and Kotseruba, Iuliia and Kunic, Toni and Tsotsos, John K.",
title = "{PIE}: A Large-Scale Dataset And Models For Pedestrian Intention Estimation And Trajectory Prediction",
booktitle = "ICCV",
year = "2019"
}
Du et al., "Unsupervised Pedestrian Pose Prediction: A Deep Predictive Coding Network-Based Approach for Autonomous Vehicle Perception", RAL, 2020. paper
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Datasets
Metrics
Bibtex
@Article{Du_2020_RAL,
author = "Du, X. and Vasudevan, R. and Johnson-Roberson, M.",
journal = "RAL",
title = "Unsupervised Pedestrian Pose Prediction: A Deep Predictive Coding Network-Based Approach for Autonomous Vehicle Perception",
year = "2020",
volume = "27",
number = "2",
pages = "129-138"
}
Bibtex
@InProceedings{Rasouli_2017_ICCVW,
author = "Rasouli, Amir and Kotseruba, Iuliia and Tsotsos, John K.",
title = "Are They Going To Cross? A Benchmark Dataset And Baseline For Pedestrian Crosswalk Behavior",
booktitle = "ICCVW",
year = "2017"
}
Dashcam Accident Dataset (DAD) link paper
Used in papers
Bao et al., "DRIVE: Deep Reinforced Accident Anticipation With Visual Explanation", ICCV, 2021. paper arxiv code
Suzuki et al., "Anticipating Traffic Accidents With Adaptive Loss And Large-Scale Incident Db", CVPR, 2018. paper arxiv
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Datasets
Metrics
Bibtex
@InProceedings{Suzuki_2018_CVPR,
author = "Suzuki, Tomoyuki and Kataoka, Hirokatsu and Aoki, Yoshimitsu and Satoh, Yutaka",
title = "Anticipating Traffic Accidents With Adaptive Loss And Large-Scale Incident Db",
booktitle = "CVPR",
year = "2018"
}
Zeng et al., "Agent-Centric Risk Assessment: Accident Anticipation And Risky Region Localization", CVPR, 2017. paper arxiv
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Datasets
Metrics
Bibtex
@InProceedings{Zeng_2017_CVPR,
author = "Zeng, Kuo-Hao and Chou, Shih-Han and Chan, Fu-Hsiang and Carlos Niebles, Juan and Sun, Min",
title = "Agent-Centric Risk Assessment: Accident Anticipation And Risky Region Localization",
booktitle = "CVPR",
year = "2017"
}
Bibtex
@InProceedings{Chan_2017_ACCV,
author = "Chan, Fu-Hsiang and Chen, Yu-Ting and Xiang, Yu and Sun, Min",
editor = "Lai, Shang-Hong and Lepetit, Vincent and Nishino, Ko and Sato, Yoichi",
title = "Anticipating Accidents In Dashcam Videos",
booktitle = "ACCV",
year = "2017"
}
JIGSAWS link paper
Used in papers
Gao et al., "Accurate Grid Keypoint Learning for Efficient Video Prediction", IROS, 2021. paper arxiv code
Weerasinghe et al., "Multimodal Transformers for Real-Time Surgical Activity Prediction", ICRA, 2024. paper arxiv code
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Datasets
Metrics
Bibtex
@inproceedings{Weerasinghe_Multimodal_2024_ICRA,
author = "Weerasinghe, Keshara and Reza Roodabeh, Seyed Hamid and Hutchinson, Kay and Alemzadeh, Homa",
booktitle = "ICRA",
title = "Multimodal Transformers for Real-Time Surgical Activity Prediction",
year = "2024"
}
Park et al., "Recognition and Prediction of Surgical Actions Based on Online Robotic Tool Detection", RAL, 2021. paper
Bibtex
@Article{Ahmidi_2017_BE,
author = "Ahmidi, Narges and Tao, Lingling and Sefati, Shahin and Gao, Yixin and Lea, Colin and Haro, Benjamín Béjar and Zappella, Luca and Khudanpur, Sanjeev and Vidal, René and Hager, Gregory D.",
journal = "IEEE Transactions on Biomedical Engineering",
title = "A Dataset and Benchmarks for Segmentation and Recognition of Gestures in Robotic Surgery",
year = "2017",
volume = "64",
number = "9",
pages = "2025-2041"
}
Something Something (SmtSmt) link paper arxiv
Used in papers
Gu et al., "Seer: Language Instructed Video Prediction with Latent Diffusion Models", ICLR, 2024. paper arxiv code
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Datasets
Metrics
Bibtex
@inproceedings{Gu_seer_2024_ICLR,
author = "Gu, Xianfan and Wen, Chuan and Ye, Weirui and Song, Jiaming and Gao, Yang",
title = "Seer: Language Instructed Video Prediction with Latent Diffusion Models",
booktitle = "ICLR",
year = "2024"
}
Chang et al., "MAU: A Motion-Aware Unit for Video Prediction and Beyond", NeurIPS, 2021. paper
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Datasets
Metrics
Bibtex
@InProceedings{Chang_2021_NeurIPS,
author = "Chang, Zheng and Zhang, Xinfeng and Wang, Shanshe and Ma, Siwei and Ye, Yan and Xinguang, Xiang and Gao, Wen",
booktitle = "NeurIPS",
title = "{MAU}: A Motion-Aware Unit for Video Prediction and Beyond",
year = "2021"
}
Stergiou et al., "The Wisdom of Crowds: Temporal Progressive Attention for Early Action Prediction", CVPR, 2023. paper arxiv code
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Datasets
Metrics
Bibtex
@InProceedings{Stergiou_2023_CVPR,
author = "Stergiou, Alexandros and Damen, Dima",
title = "The Wisdom of Crowds: Temporal Progressive Attention for Early Action Prediction",
booktitle = "CVPR",
year = "2023"
}
Bibtex
@InProceedings{Goya_2017_CVPR,
author = "Goyal, Raghav and Ebrahimi Kahou, Samira and Michalski, Vincent and Materzynska, Joanna and Westphal, Susanne and Kim, Heuna and Haenel, Valentin and Fruend, Ingo and Yianilos, Peter and Mueller-Freitag, Moritz and others",
title = "The {Something Something} Video Database for Learning and Evaluating Visual Common Sense",
booktitle = "CVPR",
year = "2017"
}
Kinetics-400 link arxiv
Used in papers
Suris et al., "Learning the Predictability of the Future", CVPR, 2021. paper arxiv code
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Datasets
Metrics
Bibtex
@InProceedings{Suris_2021_CVPR,
author = "Suris, Didac and Liu, Ruoshi and Vondrick, Carl",
title = "Learning the Predictability of the Future",
booktitle = "CVPR",
year = "2021"
}
Wang et al., "Self-supervised Video Representation Learning by Pace Prediction", ECCV, 2020. paper arxiv code
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Datasets
Metrics
Bibtex
@InProceedings{Wang_2020_ECCV_2,
author = "Wang, Jiangliu and Jiao, Jianbo and Liu, Yun-Hui",
title = "Self-supervised Video Representation Learning by Pace Prediction",
booktitle = "ECCV",
year = "2020"
}
Bibtex
@Article{Kay_2017_arxiv,
author = "Kay, Will and Carreira, Joao and Simonyan, Karen and Zhang, Brian and Hillier, Chloe and Vijayanarasimhan, Sudheendra and Viola, Fabio and Green, Tim and Back, Trevor and Natsev, Paul and Suleyman, Mustafa and Zisserman, Andrew",
title = "The Kinetics Human Action Video Dataset",
journal = "arXiv:1705.06950",
year = "2017"
}
MD17 link paper
Used in papers
Xu et al., "Uncovering the Missing Pattern: Unified Framework Towards Trajectory Imputation and Prediction", CVPR, 2023. paper arxiv code
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Datasets
Metrics
Bibtex
@InProceedings{Xu_2023_CVPR,
author = "Xu, Yi and Bazarjani, Armin and Chi, Hyung-gun and Choi, Chiho and Fu, Yun",
title = "Uncovering the Missing Pattern: Unified Framework Towards Trajectory Imputation and Prediction",
booktitle = "CVPR",
year = "2023"
}
Bibtex
@article{Chmiela_2017_SA,
author = "Chmiela, Stefan and Tkatchenko, Alexandre and Sauceda, Huziel E and Poltavsky, Igor and Schutt, Kristof T and Muller, Klaus-Robert",
title = "Machine learning of accurate energy-conserving molecular force fields",
journal = "Science Advances",
volume = "3",
number = "5",
year = "2017"
}
Mouse Fish link paper arxiv
Used in papers
Liu et al., "Motion Prediction Using Trajectory Cues", ICCV, 2021. paper code
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Datasets
Metrics
Bibtex
@InProceedings{Liu_2021_ICCV,
author = "Liu, Zhenguang and Su, Pengxiang and Wu, Shuang and Shen, Xuanjing and Chen, Haipeng and Hao, Yanbin and Wang, Meng",
title = "Motion Prediction Using Trajectory Cues",
booktitle = "ICCV",
year = "2021"
}
Liu et al., "Towards Natural And Accurate Future Motion Prediction Of Humans And Animals", CVPR, 2019. paper code
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Datasets
Metrics
Bibtex
@InProceedings{Liu_2019_CVPR,
author = "Liu, Zhenguang and Wu, Shuang and Jin, Shuyuan and Liu, Qi and Lu, Shijian and Zimmermann, Roger and Cheng, Li",
title = "Towards Natural And Accurate Future Motion Prediction Of Humans And Animals",
booktitle = "CVPR",
year = "2019"
}
Bibtex
@Article{Xu_2017_IJCV,
author = "Xu, Chi and Govindarajan, Lakshmi Narasimhan and Zhang, Yu and Cheng, Li",
title = "{Lie-X}: Depth Image Based Articulated Object Pose Estimation, Tracking, And Action Recognition On Lie Groups",
journal = "IJCV",
volume = "123",
number = "3",
pages = "454--478",
year = "2017"
}
Oxford Robot Car (ORC) link paper
Used in papers
Marchetti et al., "MANTRA: Memory Augmented Networks for Multiple Trajectory Prediction", CVPR, 2020. paper arxiv
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Datasets
Metrics
Bibtex
@InProceedings{Marchetti_2020_CVPR,
author = "Marchetti, Francesco and Becattini, Federico and Seidenari, Lorenzo and Del Bimbo, Alberto",
title = "{MANTRA}: Memory Augmented Networks for Multiple Trajectory Prediction",
booktitle = "CVPR",
year = "2020"
}
Srikanth et al., "INFER: INtermediate Representations For FuturE PRediction", IROS, 2019. paper arxiv code
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Datasets
Metrics
Bibtex
@InProceedings{Srikanth_2019_IROS,
author = "Srikanth, Shashank and Ansari, Junaid Ahmed and Sharma, Sarthak and others",
booktitle = "IROS",
title = "{INFER}: {IN}termediate Representations For {F}utur{E} P{R}ediction",
year = "2019"
}
Bibtex
@Article{Maddern_2017_IJRR,
Author = "Maddern, Will and Pascoe, Geoff and Linegar, Chris and Newman, Paul",
Title = "1 Year, 1000Km: The {O}xford Robotcar Dataset",
Journal = "IJRR",
Volume = "36",
Number = "1",
Pages = "3-15",
Year = "2017"
}
PKU-MMD link arxiv
Used in papers
Liu et al., "SSNet: Scale Selection Network For Online 3D Action Prediction", CVPR, 2018. paper
Mao et al., "Masked Motion Predictors are Strong 3D Action Representation Learners", ICCV, 2023. paper arxiv code
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Datasets
Metrics
Bibtex
@InProceedings{Mao_2023_ICCV,
author = "Mao, Yunyao and Deng, Jiajun and Zhou, Wengang and Fang, Yao and Ouyang, Wanli and Li, Houqiang",
title = "Masked Motion Predictors are Strong 3D Action Representation Learners",
booktitle = "ICCV",
year = "2023"
}
Bibtex
@Article{Liu_2017_arxiv,
author = "Chunhui, Liu and Yueyu, Hu and Yanghao, Li and Sijie, Song and Jiaying, Liu",
title = "{PKU-MMD}: A Large Scale Benchmark For Continuous Multi-Modal Human Action Understanding",
journal = "arXiv:1703.07475",
year = "2017"
}
Recipe1M link paper arxiv
Used in papers
Abdelsalam et al., "GePSAn: Generative Procedure Step Anticipation in Cooking Videos", ICCV, 2023. paper
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Datasets
Metrics
Bibtex
@InProceedings{Abdelsalam_2023_ICCV,
author = "Abdelsalam, Mohamed A. and Rangrej, Samrudhdhi B. and Hadji, Isma and Dvornik, Nikita and Derpanis, Konstantinos G. and Fazly, Afsaneh",
title = "GePSAn: Generative Procedure Step Anticipation in Cooking Videos",
booktitle = "ICCV",
year = "2023"
}
Bibtex
@InProceedings{Salvador_2017_CVPR,
author = "Salvador, Amaia and Hynes, Nicholas and Aytar, Yusuf and Marin, Javier and Ofli, Ferda and Weber, Ingmar and Torralba, Antonio",
title = "Learning Cross-Modal Embeddings For Cooking Recipes And Food Images",
booktitle = "CVPR",
year = "2017"
}
L-CAS link paper
Used in papers
Sun et al., "3Dof Pedestrian Trajectory Prediction Learned From Long-Term Autonomous Mobile Robot Deployment Data", ICRA, 2018. paper arxiv
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Datasets
Metrics
Bibtex
@InProceedings{Sun_2018_ICRA,
author = "Sun, L. and Yan, Z. and Mellado, S. M. and Hanheide, M. and Duckett, T.",
booktitle = "ICRA",
title = "{3Dof} Pedestrian Trajectory Prediction Learned From Long-Term Autonomous Mobile Robot Deployment Data",
year = "2018"
}
Bibtex
@InProceedings{Yan_2017_IROS,
author = "Yan, Zhi and Duckett, Tom and Bellotto, Nicola",
title = "Online Learning For Human Classification In {3D} Lidar-Based Tracking",
booktitle = "IROS",
year = "2017"
}
Epic-Fail link paper arxiv
Used in papers
Zeng et al., "Agent-Centric Risk Assessment: Accident Anticipation And Risky Region Localization", CVPR, 2017. paper arxiv
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Datasets
Metrics
Bibtex
@InProceedings{Zeng_2017_CVPR,
author = "Zeng, Kuo-Hao and Chou, Shih-Han and Chan, Fu-Hsiang and Carlos Niebles, Juan and Sun, Min",
title = "Agent-Centric Risk Assessment: Accident Anticipation And Risky Region Localization",
booktitle = "CVPR",
year = "2017"
}
Bibtex
@InProceedings{Zeng_2017_CVPR,
author = "Zeng, Kuo-Hao and Chou, Shih-Han and Chan, Fu-Hsiang and Carlos Niebles, Juan and Sun, Min",
title = "Agent-Centric Risk Assessment: Accident Anticipation And Risky Region Localization",
booktitle = "CVPR",
year = "2017"
}
CityPersons link paper arxiv
Used in papers
Bhattacharyya et al., "Long-Term On-Board Prediction Of People In Traffic Scenes Under Uncertainty", CVPR, 2018. paper arxiv code
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Datasets
Metrics
Bibtex
@InProceedings{Bhattacharyya_2018_CVPR,
author = "Bhattacharyya, Apratim and Fritz, Mario and Schiele, Bernt",
title = "Long-Term On-Board Prediction Of People In Traffic Scenes Under Uncertainty",
booktitle = "CVPR",
year = "2018"
}
Bibtex
@InProceedings{Shanshan_2017_CVPR,
Author = "Zhang, Shanshan and Benenson, Rodrigo and Schiele, Bernt",
Title = "Citypersons: A Diverse Dataset For Pedestrian Detection",
Booktitle = "CVPR",
Year = "2017"
}
STRANDS link paper arxiv
Used in papers
Sun et al., "3Dof Pedestrian Trajectory Prediction Learned From Long-Term Autonomous Mobile Robot Deployment Data", ICRA, 2018. paper arxiv
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Datasets
Metrics
Bibtex
@InProceedings{Sun_2018_ICRA,
author = "Sun, L. and Yan, Z. and Mellado, S. M. and Hanheide, M. and Duckett, T.",
booktitle = "ICRA",
title = "{3Dof} Pedestrian Trajectory Prediction Learned From Long-Term Autonomous Mobile Robot Deployment Data",
year = "2018"
}
Bibtex
@Article{Hawes_2017_RAM,
author = "Hawes, Nick and Burbridge, Christopher and Jovan, Ferdian and Kunze, Lars and Lacerda, Bruno and Mudrova, Lenka and Young, Jay and Wyatt, Jeremy and Hebesberger, Denise and Kortner, Tobias and others",
title = "The Strands Project: Long-Term Autonomy In Everyday Environments",
journal = "IEEE Robotics \\\& Automation Magazine",
volume = "24",
number = "3",
pages = "146--156",
year = "2017"
}
Mapillary Vistas link paper
Used in papers
Makansi et al., "Multimodal Future Localization and Emergence Prediction for Objects in Egocentric View With a Reachability Prior", CVPR, 2020. paper arxiv code
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Datasets
Metrics
Bibtex
@InProceedings{Makansi_2020_CVPR,
author = "Makansi, Osama and Cicek, Ozgun and Buchicchio, Kevin and Brox, Thomas",
title = "Multimodal Future Localization and Emergence Prediction for Objects in Egocentric View With a Reachability Prior",
booktitle = "CVPR",
year = "2020"
}
Bibtex
@InProceedings{Neuhold_2017_ICCV,
author = "Neuhold, Gerhard and Ollmann, Tobias and Rota Bulo, Samuel and Kontschieder, Peter",
title = "The Mapillary Vistas Dataset for Semantic Understanding of Street Scenes",
booktitle = "ICCV",
year = "2017"
}
Matterport3D link paper arxiv
Used in papers
Ramakrishnan et al., "Occupancy Anticipation for Efficient Exploration and Navigation", ECCV, 2020. paper arxiv code
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Datasets
Metrics
Bibtex
@InProceedings{Ramakrishnan_2020_ECCV,
author = "Ramakrishnan, Santhosh K and Al-Halah, Ziad and Grauman, Kristen",
title = "Occupancy Anticipation for Efficient Exploration and Navigation",
booktitle = "ECCV",
year = "2020"
}
Bibtex
@InProceedings{Chang_2017_3DV,
author = "Chang, Angel and Dai, Angela and Funkhouser, Thomas and Halber, Maciej and Niessner, Matthias and Savva, Manolis and Song, Shuran and Zeng, Andy and Zhang, Yinda",
title = "{Matterport3D}: Learning from {RGB-D} Data in Indoor Environments",
booktitle = "3DV",
year = "2017"
}
Berkeley DeepDrive (BDD100K) link paper arxiv
Used in papers
Schmeckpeper et al., "Learning Predictive Models From Observation and Interaction", ECCV, 2020. paper arxiv
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Datasets
Metrics
Bibtex
@InProceedings{Schmeckpeper_2020_ECCV,
author = "Schmeckpeper, Karl and Xie, Annie and Rybkin, Oleh and Tian, Stephen and Daniilidis, Kostas and Levine, Sergey and Finn, Chelsea",
title = "Learning Predictive Models From Observation and Interaction",
booktitle = "ECCV",
year = "2020"
}
Bibtex
@InProceedings{Xu_2017_CVPR,
author = "Xu, Huazhe and Gao, Yang and Yu, Fisher and Darrell, Trevor",
title = "End-To-End Learning of Driving Models From Large-Scale Video Datasets",
booktitle = "CVPR",
year = "2017"
}
20BN link paper arxiv
Used in papers
Rothfuss et al., "Deep Episodic Memory: Encoding, Recalling, and Predicting Episodic Experiences for Robot Action Execution", RAL, 2018. paper arxiv
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Datasets
Metrics
Bibtex
@Article{Rothfuss_2018_RAL,
author = "Rothfuss, J. and Ferreira, F. and Aksoy, E. E. and Zhou, Y. and Asfour, T.",
journal = "RAL",
title = "Deep Episodic Memory: Encoding, Recalling, and Predicting Episodic Experiences for Robot Action Execution",
year = "2018",
volume = "3",
number = "4",
pages = "4007-4014"
}
Bibtex
@InProceedings{Goyal_2017_ICCV,
author = "Goyal, Raghav and Kahou, Samira Ebrahimi and Michalski, Vincent and Materzynska, Joanna and Westphal, Susanne and Kim, Heuna and Haenel, Valentin and Fruend, Ingo and Yianilos, Peter and Mueller-Freitag, Moritz and others",
title = "The Something Something Video Database for Learning and Evaluating Visual Common Sense.",
booktitle = "ICCV",
year = "2017"
}
DFAUST link paper
Used in papers
Bibtex
@InProceedings{Bogo_2017_CVPR,
author = "Bogo, Federica and Romero, Javier and Pons-Moll, Gerard and Black, Michael J.",
title = "Dynamic {FAUST}: Registering Human Bodies in Motion",
booktitle = "CVPR",
year = "2017"
}
DAVIS17 link arxiv
Used in papers
Hu et al., "A Dynamic Multi-Scale Voxel Flow Network for Video Prediction", CVPR, 2023. paper arxiv code
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Datasets
Metrics
Bibtex
@InProceedings{Hu_2023_CVPR,
author = "Hu, Xiaotao and Huang, Zhewei and Huang, Ailin and Xu, Jun and Zhou, Shuchang",
title = "A Dynamic Multi-Scale Voxel Flow Network for Video Prediction",
booktitle = "CVPR",
year = "2023"
}
Bibtex
@article{Pont_2017_Arxiv,
author = "Pont-Tuset, Jordi and Perazzi, Federico and Caelles, Sergi and Arbelaez, Pablo and Sorkine-Hornung, Alex and Van Gool, Luc",
title = "The 2017 davis challenge on video object segmentation",
journal = "arXiv:1704.00675",
year = "2017"
}
BU Action (BUA) link paper arxiv
Used in papers
Safaei et al., "Still Image Action Recognition By Predicting Spatial-Temporal Pixel Evolution", WACV, 2019. paper
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Datasets
Metrics
Bibtex
@InProceedings{Safaei_2019_WACV,
author = "Safaei, M. and Foroosh, H.",
booktitle = "WACV",
title = "Still Image Action Recognition By Predicting Spatial-Temporal Pixel Evolution",
year = "2019"
}
Bibtex
@Article{Ma_2017_PR,
author = "Ma, Shugao and Bargal, Sarah Adel and Zhang, Jianming and Sigal, Leonid and Sclaroff, Stan",
title = "Do Less And Achieve More: Training Cnns For Action Recognition Utilizing Action Images From The Web",
journal = "Pattern Recognition",
volume = "68",
pages = "334--345",
year = "2017"
}
- Summary: A dataset of pedestrians and cyclists movements recorded using an aerial drone with 3K+ tracks
- Applications: Trajectory prediction
- Data type and annotations: RGB, bounding box, object class, Tracking ID
- Task: Surveillance
- SDD
- Custom
- Argoverse
- SDD
- INTERACTION
- Custom
- SDD
- Custom
- Summary: A motion dataset consists of various activities including human interaction, interaction with the environment, locomotion, sports, etc.
- Applications: Action prediction, Motion prediction
- Data type and annotations: 3D pose, activity label
- Task: Activity
- Summary: A driving dataset of street images with annotations for 30 traffic objects in 5k frames and weak annotations in 20k frames
- Applications: Video prediction, Trajectory prediction, Other prediction
- Data type and annotations: Stereo RGB, bounding box, semantic segment, vehicle sensors
- Task: Driving
- Cityscapes
- Custom
- Summary: A dataset of trajectories of NBA players from games at a given season.
- Applications: Trajectory prediction
- Data type and annotations: Trajectory
- Task: Sport
- Summary: An action dataset of 60 daily activities in 56K+ video samples
- Applications: Action prediction
- Data type and annotations: RGBD, IR, 3D pose, activity label
- Task: Activity
- NTU RGB-D
- Custom
- Summary: A dataset of object manipulation using a robot arm with 59k object pushing motion samples
- Applications: Video prediction
- Data type and annotations: RGB
- Task: Robot object manipulation
- Summary: A dataset of 80K+ images collected from 21K+ sequences with corresponding text captions
- Applications: Other prediction
- Data type and annotations: RGB, text
- Task: Visual story
- Summary: A dataset of 20K genomics for 33 types of cancers.
- Applications: Other prediction
- Data type and annotations: RGB, Label
- Task: Risk assessment
- Summary: A collection of sequences collected from TV series for the purpose of action detection
- Applications: Action prediction
- Data type and annotations: RGB, activity label, temporal segment
- Task: Activity
- Summary: A dataset of 10 indoor activities in 59 sequences collected using a Kinect V2 sensor
- Applications: Action prediction
- Data type and annotations: RGBD, 3D pose, activity label, temporal segment, Tracking ID
- Task: Activity
- Summary: A dataset of 450+ activities, such as cooking, house chores, etc., videos collected from public video sharing websites
- Applications: Action prediction
- Data type and annotations: RGB, activity label
- Task: Activity
- Summary: A large-scale dataset of videos collected from YouTube with corresponding machine-generated annotations from a vocabulary of 3.8K+ visual entities
- Applications: Video prediction
- Data type and annotations: RGB, activity label, temporal segment
- Task: Activity
- Summary: A dataset of catwalks by Miss Universe contestants during the evening gown competition from 1996 to 2010
- Applications: Other prediction
- Data type and annotations: RGB, bounding box, scores
- Task: Miss universe
- Summary: A simulated dataset of bounding balls generated using Neural Physics Engine
- Applications: Video prediction
- Data type and annotations: RGB
- Task: Object (simulation)
- Summary: A dataset of ~10K indoor videos with 157 action and 46 object classes
- Applications: Action prediction
- Data type and annotations: RGB, Activity label, Object Class, Temporal segment
- Task: Activity
- Summary: A dataset of 4830 frames from 55 videos with 9 player action labels and 8 team activity labels
- Applications: Action prediction, Trajectory prediction
- Data type and annotations: RGB, Activity label, Bounding box
- Task: Sport
- Summary: A dataset of Ceilidh Scottish dance sequences performed by 16 dancers in two styles recorded from bird’s eye view.
- Applications: Action prediction, Trajectory prediction
- Data type and annotations: RGB, Activity Label, Trajectory
- Task: Activity
- Ceilidh Dance
- Custom
- Summary: A dataset of randomized 3D trajectories generated using 25K synthetic stereo frames.
- Applications:
- Data type and annotations: RGBD
- Task: Object (simulation)
- Summary: A dataset of 6.7K recordings of human-object interactions performed by 53 subjects.
- Applications: Motion prediction
- Data type and annotations: 3D Pose, Activity Label
- Task: Pose
Stanford Drone Dataset (SDD) link paper
Used in papers
Bae et al., "Can Language Beat Numerical Regression? Language-Based Multimodal Trajectory Prediction", CVPR, 2024. paper arxiv code
Wong et al., "SocialCircle: Learning the Angle-based Social Interaction Representation for Pedestrian Trajectory Prediction", CVPR, 2024. paper arxiv code
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Datasets
Metrics
Bibtex
@InProceedings{Wong_SocialCircle_2024_CVPR,
author = "Wong, Conghao and Xia, Beihao and Zou, Ziqian and Wang, Yulong and You, Xinge",
title = "SocialCircle: Learning the Angle-based Social Interaction Representation for Pedestrian Trajectory Prediction",
booktitle = "CVPR",
year = "2024"
}
Kim et al., "Higher-order Relational Reasoning for Pedestrian Trajectory Prediction", CVPR, 2024. paper
-
Datasets
Metrics
Bibtex
@InProceedings{Kim_Higher_2024_CVPR,
author = "Kim, Sungjune and Chi, Hyung-gun and Lim, Hyerin and Ramani, Karthik and Kim, Jinkyu and Kim, Sangpil",
title = "Higher-order Relational Reasoning for Pedestrian Trajectory Prediction",
booktitle = "CVPR",
year = "2024"
}
Lin et al., "DyHGDAT: Dynamic Hypergraph Dual Attention Network for multi-agent trajectory prediction", ICRA, 2024. paper
-
Datasets
Metrics
Bibtex
@inproceedings{Lin_DyHGDAT_2024_ICRA,
author = "Lin, Weilong and Zeng, Xinhua and Pang, Chengxin and Teng, Jing and Liu, Jing",
booktitle = "ICRA",
title = "DyHGDAT: Dynamic Hypergraph Dual Attention Network for multi-agent trajectory prediction",
year = "2024"
}
Chen et al., "Goal-Guided and Interaction-Aware State Refinement Graph Attention Network for Multi-Agent Trajectory Prediction", RAL, 2024. paper
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Datasets
Metrics
Bibtex
@ARTICLE{Chen_Goal_2024_RAL,
author = "Chen, Xiaobo and Luo, Fengbo and Zhao, Feng and Ye, Qiaolin",
journal = "RAL",
title = "Goal-Guided and Interaction-Aware State Refinement Graph Attention Network for Multi-Agent Trajectory Prediction",
year = "2024",
volume = "9",
number = "1",
pages = "57-64",
keywords = "Trajectory;Predictive models;Feature extraction;Transformers;Generative adversarial networks;Behavioral sciences;Task analysis;Graph attention;multi-agent trajectory prediction;multimodal prediction;state refinement",
doi = "10.1109/LRA.2023.3331651"
}
Mao et al., "Leapfrog Diffusion Model for Stochastic Trajectory Prediction", CVPR, 2023. paper arxiv code
Bae et al., "EigenTrajectory: Low-Rank Descriptors for Multi-Modal Trajectory Forecasting", ICCV, 2023. paper arxiv code
Dong et al., "Sparse Instance Conditioned Multimodal Trajectory Prediction", ICCV, 2023. paper
Maeda et al., "Fast Inference and Update of Probabilistic Density Estimation on Trajectory Prediction", ICCV, 2023. paper arxiv code
Shi et al., "Trajectory Unified Transformer for Pedestrian Trajectory Prediction", ICCV, 2023. paper
Weng et al., "Joint Metrics Matter: A Better Standard for Trajectory Forecasting", ICCV, 2023. paper arxiv code
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Datasets
Metrics
Bibtex
@InProceedings{Weng_2023_ICCV,
author = "Weng, Erica and Hoshino, Hana and Ramanan, Deva and Kitani, Kris",
title = "Joint Metrics Matter: A Better Standard for Trajectory Forecasting",
booktitle = "ICCV",
year = "2023"
}
Zhang et al., "TrajPAC: Towards Robustness Verification of Pedestrian Trajectory Prediction Models", ICCV, 2023. paper arxiv
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Datasets
Metrics
Bibtex
@InProceedings{Zhang_2023_ICCV,
author = "Zhang, Liang and Xu, Nathaniel and Yang, Pengfei and Jin, Gaojie and Huang, Cheng-Chao and Zhang, Lijun",
title = "TrajPAC: Towards Robustness Verification of Pedestrian Trajectory Prediction Models",
booktitle = "ICCV",
year = "2023"
}
Huang et al., "HyperTraj: Towards Simple and Fast Scene-Compliant Endpoint Conditioned Trajectory Prediction", IROS, 2023. paper
Bae et al., "Non-Probability Sampling Network for Stochastic Human Trajectory Prediction", CVPR, 2022. paper arxiv code
Gu et al., "Stochastic Trajectory Prediction via Motion Indeterminacy Diffusion", CVPR, 2022. paper arxiv code
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Datasets
Metrics
Bibtex
@InProceedings{Gu_2022_CVPR,
author = "Gu, Tianpei and Chen, Guangyi and Li, Junlong and Lin, Chunze and Rao, Yongming and Zhou, Jie and Lu, Jiwen",
title = "Stochastic Trajectory Prediction via Motion Indeterminacy Diffusion",
booktitle = "CVPR",
year = "2022"
}
Guo et al., "End-to-End Trajectory Distribution Prediction Based on Occupancy Grid Maps", CVPR, 2022. paper arxiv code
Monti et al., "How Many Observations Are Enough? Knowledge Distillation for Trajectory Forecasting", CVPR, 2022. paper arxiv
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Datasets
Metrics
Bibtex
@InProceedings{Monti_2022_CVPR,
author = "Monti, Alessio and Porrello, Angelo and Calderara, Simone and Coscia, Pasquale and Ballan, Lamberto and Cucchiara, Rita",
title = "How Many Observations Are Enough? Knowledge Distillation for Trajectory Forecasting",
booktitle = "CVPR",
year = "2022"
}
Xu et al., "Remember Intentions: Retrospective-Memory-Based Trajectory Prediction", CVPR, 2022. paper arxiv code
Sun et al., "Human Trajectory Prediction With Momentary Observation", CVPR, 2022. paper
Bae et al., "Learning Pedestrian Group Representations for Multi-modal Trajectory Prediction", ECCV, 2022. paper arxiv code
Tsao et al., "Social-SSL: Self-Supervised Cross-Sequence Representation Learning Based on Transformers for Multi-agent Trajectory Prediction", ECCV, 2022. paper code
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Datasets
Metrics
Bibtex
@InProceedings{Tsao_2022_ECCV,
author = "Tsao, Li-Wu and Wang, Yan-Kai and Lin, Hao-Siang and Shuai, Hong-Han and Wong, Lai-Kuan and Cheng, Wen-Huang",
title = "{Social-SSL}: Self-Supervised Cross-Sequence Representation Learning Based on Transformers for Multi-agent Trajectory Prediction",
booktitle = "ECCV",
year = "2022"
}
Wong et al., "View Vertically: A Hierarchical Network for Trajectory Prediction via Fourier Spectrums", ECCV, 2022. paper arxiv code
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Datasets
Metrics
Bibtex
@InProceedings{Wong_2022_ECCV,
author = "Wong, Conghao and Xia, Beihao and Hong, Ziming and Peng, Qinmu and Yuan, Wei and Cao, Qiong and Yang, Yibo and You, Xinge",
title = "View Vertically: A Hierarchical Network for Trajectory Prediction via Fourier Spectrums",
booktitle = "ECCV",
year = "2022"
}
Xu et al., "SocialVAE: Human Trajectory Prediction Using Timewise Latents", ECCV, 2022. paper arxiv code
Zhang et al., "D2-TPred: Discontinuous Dependency for Trajectory Prediction under Traffic Lights", ECCV, 2022. paper arxiv code
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Datasets
Metrics
Bibtex
@InProceedings{Zhang_2022_ECCV,
author = "Zhang, Yuzhen and Wang, Wentong and Guo, Weizhi and Lv, Pei and Xu, Mingliang and Chen, Wei and Manocha, Dinesh",
title = "{D2-TPred}: Discontinuous Dependency for Trajectory Prediction under Traffic Lights",
booktitle = "ECCV",
year = "2022"
}
Kothari et al., "Motion Style Transfer: Modular Low-Rank Adaptation for Deep Motion Forecasting", CoRL, 2022. paper arxiv code
Meng et al., "Forecasting Human Trajectory from Scene History", NeurIPS, 2022. paper arxiv code
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Datasets
Metrics
Bibtex
@InProceedings{Meng_2022_NeurIPS,
author = "Meng, Mancheng and Wu, Ziyan and Chen, Terrence and Cai, Xiran and Zhou, Xiang Sean and Yang, Fan and Shen, Dinggang",
title = "Forecasting Human Trajectory from Scene History",
booktitle = "NeurIPS",
year = "2022"
}
Xie et al., "Synchronous Bi-Directional Pedestrian Trajectory Prediction with Error Compensation", ACCV, 2022. paper
Sun et al., "Unified and Fast Human Trajectory Prediction Via Conditionally Parameterized Normalizing Flow", RAL, 2022. paper
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Datasets
Metrics
Bibtex
@ARTICLE{Sun_Unified_2022_RAL,
author = "Sun, Jianhua and Wang, Zehao and Li, Jiefeng and Lu, Cewu",
journal = "RAL",
title = "Unified and Fast Human Trajectory Prediction Via Conditionally Parameterized Normalizing Flow",
year = "2022",
volume = "7",
number = "2",
pages = "842-849"
}
Zhao et al., "Where Are You Heading? Dynamic Trajectory Prediction With Expert Goal Examples", ICCV, 2021. paper code
Liang et al., "SimAug: Learning Robust Representations from Simulation for Trajectory Prediction", ECCV, 2020. paper arxiv code
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Datasets
Metrics
Bibtex
@InProceedings{Liang_2020_ECCV,
author = "Liang, Junwei and Jiang, Lu and Hauptmann, Alexander",
title = "{SimAug}: Learning Robust Representations from Simulation for Trajectory Prediction",
booktitle = "ECCV",
year = "2020"
}
Tao et al., "Dynamic and Static Context-aware LSTM for Multi-agent Motion Prediction", ECCV, 2020. paper arxiv
Li et al., "EvolveGraph: Multi-Agent Trajectory Prediction with Dynamic Relational Reasoning", NeurIPS, 2020. paper arxiv
Dendorfer et al., "Goal-GAN: Multimodal Trajectory Prediction Based on Goal Position Estimation", ACCV, 2020. paper arxiv code
Berlati et al., "Ambiguity in Sequential Data: Predicting Uncertain Futures With Recurrent Models", RAL, 2020. paper arxiv
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Datasets
Bibtex
@Article{Berlati_2020_RAL,
author = "Berlati, A. and Scheel, O. and Stefano, L. D. and Tombari, F.",
journal = "RAL",
title = "Ambiguity in Sequential Data: Predicting Uncertain Futures With Recurrent Models",
year = "2020",
volume = "5",
number = "2",
pages = "2935-2942"
}
Ridel et al., "Scene Compliant Trajectory Forecast With Agent-Centric Spatio-Temporal Grids", RAL, 2020. paper arxiv
Choi et al., "DROGON: A Trajectory Prediction Model Based on Intention-conditioned Behavior Reasoning", CoRL, 2020. paper arxiv
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Datasets
Metrics
Bibtex
@InProceedings{Choi_2020_CORL,
author = "Choi, Chiho and Malla, Srikanth and Patil, Abhishek and Choi, J Hee",
title = "{DROGON}: A Trajectory Prediction Model Based on Intention-conditioned Behavior Reasoning",
booktitle = "CoRL",
year = "2020"
}
Zhao et al., "TNT: Target-driven Trajectory Prediction", CoRL, 2020. paper arxiv
-
Datasets
Bibtex
@InProceedings{Zhao_2020_CORL,
author = "Zhao, Hang and Gao, Jiyang and Lan, Tian and Sun, Chen and Sapp, Benjamin and Varadarajan, Balakrishnan and Shen, Yue and Shen, Yi and Chai, Yuning and Schmid, Cordelia and others",
title = "{TNT}: Target-driven Trajectory Prediction",
booktitle = "CoRL",
year = "2020"
}
Makansi et al., "Overcoming Limitations of Mixture Density Networks: A Sampling and Fitting Framework for Multimodal Future Prediction", CVPR, 2019. paper arxiv code
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Datasets
Metrics
Bibtex
@InProceedings{Makansi_2019_CVPR,
author = "Makansi, Osama and Ilg, Eddy and Cicek, Ozgun and Brox, Thomas",
title = "Overcoming Limitations of Mixture Density Networks: A Sampling and Fitting Framework for Multimodal Future Prediction",
booktitle = "CVPR",
year = "2019"
}
Zhao et al., "Multi-Agent Tensor Fusion For Contextual Trajectory Prediction", CVPR, 2019. paper arxiv
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Datasets
Metrics
Bibtex
@InProceedings{Zhao_2019_CVPR,
author = "Zhao, Tianyang and Xu, Yifei and Monfort, Mathew and Choi, Wongun and Baker, Chris and Zhao, Yibiao and Wang, Yizhou and Wu, Ying Nian",
title = "Multi-Agent Tensor Fusion For Contextual Trajectory Prediction",
booktitle = "CVPR",
year = "2019"
}
Li et al., "Conditional Generative Neural System For Probabilistic Trajectory Prediction", IROS, 2019. paper arxiv
Xue et al., "Location-Velocity Attention For Pedestrian Trajectory Prediction", WACV, 2019. paper
Bhattacharyya et al., "Accurate and Diverse Sampling of Sequences based on a “best of many” Sample Objective", CVPR, 2018. paper arxiv
Sadeghian et al., "CAR-Net: Clairvoyant Attentive Recurrent Network", ECCV, 2018. paper arxiv
-
Datasets
Bibtex
@InProceedings{Sadeghian_2018_ECCV,
author = "Sadeghian, Amir and Legros, Ferdinand and Voisin, Maxime and Vesel, Ricky and Alahi, Alexandre and Savarese, Silvio",
title = "{CAR-Net}: Clairvoyant Attentive Recurrent Network",
booktitle = "ECCV",
year = "2018"
}
Lee et al., "DESIRE: Distant Future Prediction In Dynamic Scenes With Interacting Agents", CVPR, 2017. paper arxiv code
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Datasets
Metrics
Bibtex
@InProceedings{Lee_2017_CVPR,
author = "Lee, Namhoon and Choi, Wongun and Vernaza, Paul and Choy, Christopher B. and Torr, Philip H. S. and Chandraker, Manmohan",
title = "{DESIRE}: Distant Future Prediction In Dynamic Scenes With Interacting Agents",
booktitle = "CVPR",
year = "2017"
}
Ballan et al., "Knowledge Transfer For Scene-Specific Motion Prediction", ECCV, 2016. paper arxiv
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Datasets
Metrics
Bibtex
@InProceedings{Ballan_2016_ECCV,
author = "Ballan, Lamberto and Castaldo, Francesco and Alahi, Alexandre and Palmieri, Francesco and Savarese, Silvio",
editor = "Leibe, Bastian and Matas, Jiri and Sebe, Nicu and Welling, Max",
title = "Knowledge Transfer For Scene-Specific Motion Prediction",
booktitle = "ECCV",
year = "2016"
}
Bibtex
@InProceedings{Robicquet_2016_ECCV,
author = "Robicquet, Alexandre and Sadeghian, Amir and Alahi, Alexandre and Savarese, Silvio",
title = "Learning Social Etiquette: Human Trajectory Understanding in Crowded Scenes",
booktitle = "ECCV",
year = "2016"
}
CMU Mocap link
Used in papers
Butepage et al., "Deep Representation Learning For Human Motion Prediction And Classification", CVPR, 2017. paper arxiv
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Datasets
Metrics
Bibtex
@InProceedings{Butepage_2017_CVPR,
author = "Butepage, Judith and Black, Michael J. and Kragic, Danica and Kjellstrom, Hedvig",
title = "Deep Representation Learning For Human Motion Prediction And Classification",
booktitle = "CVPR",
year = "2017"
}
Dax et al., "Disentangled Neural Relational Inference for Interpretable Motion Prediction", RAL, 2024. paper arxiv
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Datasets
Metrics
Bibtex
@ARTICLE{Dax_Disentangled_2024_RAL,
author = "Dax, Victoria M. and Li, Jiachen and Sachdeva, Enna and Agarwal, Nakul and Kochenderfer, Mykel J.",
journal = "RAL",
title = "Disentangled Neural Relational Inference for Interpretable Motion Prediction",
year = "2024",
volume = "9",
number = "2",
pages = "1452-1459",
keywords = "Predictive models;Trajectory;Vehicle dynamics;Decoding;Data models;Computational modeling;Training;AI-Based Methods;Behavior-Based Systems;Probabilistic Inference",
doi = "10.1109/LRA.2023.3342554"
}
Sun et al., "MoML: Online Meta Adaptation for 3D Human Motion Prediction", CVPR, 2024. paper
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Datasets
Metrics
Bibtex
@InProceedings{Sun_MoML_2024_CVPR,
author = "Sun, Xiaoning and Sun, Huaijiang and Li, Bin and Wei, Dong and Li, Weiqing and Lu, Jianfeng",
title = "MoML: Online Meta Adaptation for 3D Human Motion Prediction",
booktitle = "CVPR",
year = "2024"
}
Yu et al., "Pose-Transformed Equivariant Network for 3D Point Trajectory Prediction", CVPR, 2024. paper code
Chen et al., "Rethinking Human Motion Prediction with Symplectic Integral", CVPR, 2024. paper code
-
Datasets
Metrics
Bibtex
@InProceedings{Chen_Rethinking_2024_CVPR,
author = "Chen, Haipeng and Lyu, Kedi and Liu, Zhenguang and Yin, Yifang and Yang, Xun and Lyu, Yingda",
title = "Rethinking Human Motion Prediction with Symplectic Integral",
booktitle = "CVPR",
year = "2024"
}
Jeong et al., "Multi-agent Long-term 3D Human Pose Forecasting via Interaction-aware Trajectory Conditioning", CVPR, 2024. paper arxiv code
Gao et al., "Decompose More and Aggregate Better: Two Closer Looks at Frequency Representation Learning for Human Motion Prediction", CVPR, 2023. paper
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Datasets
Metrics
Bibtex
@InProceedings{Gao_2023_CVPR,
author = "Gao, Xuehao and Du, Shaoyi and Wu, Yang and Yang, Yang",
title = "Decompose More and Aggregate Better: Two Closer Looks at Frequency Representation Learning for Human Motion Prediction",
booktitle = "CVPR",
year = "2023"
}
Peng et al., "Trajectory-Aware Body Interaction Transformer for Multi-Person Pose Forecasting", CVPR, 2023. paper arxiv code
Tanke et al., "Social Diffusion: Long-term Multiple Human Motion Anticipation", ICCV, 2023. paper
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Datasets
Metrics
Bibtex
@InProceedings{Tanke_2023_ICCV,
author = "Tanke, Julian and Zhang, Linguang and Zhao, Amy and Tang, Chengcheng and Cai, Yujun and Wang, Lezi and Wu, Po-Chen and Gall, Juergen and Keskin, Cem",
title = "Social Diffusion: Long-term Multiple Human Motion Anticipation",
booktitle = "ICCV",
year = "2023"
}
Xu et al., "Joint-Relation Transformer for Multi-Person Motion Prediction", ICCV, 2023. paper arxiv code
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Datasets
Metrics
Bibtex
@InProceedings{Xu_2023_ICCV,
author = "Xu, Qingyao and Mao, Weibo and Gong, Jingze and Xu, Chenxin and Chen, Siheng and Xie, Weidi and Zhang, Ya and Wang, Yanfeng",
title = "Joint-Relation Transformer for Multi-Person Motion Prediction",
booktitle = "ICCV",
year = "2023"
}
Chen et al., "HumanMAC: Masked Motion Completion for Human Motion Prediction", ICCV, 2023. paper arxiv code
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Datasets
Metrics
Bibtex
@InProceedings{Chen_2023_ICCV_1,
author = "Chen, Ling-Hao and Zhang, JiaWei and Li, Yewen and Pang, Yiren and Xia, Xiaobo and Liu, Tongliang",
title = "HumanMAC: Masked Motion Completion for Human Motion Prediction",
booktitle = "ICCV",
year = "2023"
}
Xu et al., "Auxiliary Tasks Benefit 3D Skeleton-based Human Motion Prediction", ICCV, 2023. paper arxiv code
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Datasets
Metrics
Bibtex
@InProceedings{Xu_2023_ICCV_1,
author = "Xu, Chenxin and Tan, Robby T. and Tan, Yuhong and Chen, Siheng and Wang, Xinchao and Wang, Yanfeng",
title = "Auxiliary Tasks Benefit 3D Skeleton-based Human Motion Prediction",
booktitle = "ICCV",
year = "2023"
}
Ma et al., "Progressively Generating Better Initial Guesses Towards Next Stages for High-Quality Human Motion Prediction", CVPR, 2022. paper arxiv code
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Datasets
Metrics
Bibtex
@InProceedings{Ma_2022_CVPR,
author = "Ma, Tiezheng and Nie, Yongwei and Long, Chengjiang and Zhang, Qing and Li, Guiqing",
title = "Progressively Generating Better Initial Guesses Towards Next Stages for High-Quality Human Motion Prediction",
booktitle = "CVPR",
year = "2022"
}
Li et al., "Skeleton-Parted Graph Scattering Networks for 3D Human Motion Prediction", ECCV, 2022. paper arxiv code
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Datasets
Metrics
Bibtex
@InProceedings{Li_2022_ECCV,
author = "Li, Maosen and Chen, Siheng and Zhang, Zijing and Xie, Lingxi and Tian, Qi and Zhang, Ya",
title = "Skeleton-Parted Graph Scattering Networks for {3D} Human Motion Prediction",
booktitle = "ECCV",
year = "2022"
}
Sun et al., "Overlooked Poses Actually Make Sense: Distilling Privileged Knowledge for Human Motion Prediction", ECCV, 2022. paper arxiv
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Datasets
Metrics
Bibtex
@InProceedings{Sun_2022_ECCV,
author = "Sun, Xiaoning and Cui, Qiongjie and Sun, Huaijiang and Li, Bin and Li, Weiqing and Lu, Jianfeng",
title = "Overlooked Poses Actually Make Sense: Distilling Privileged Knowledge for Human Motion Prediction",
booktitle = "ECCV",
year = "2022"
}
Wang et al., "Multi-Person 3D Motion Prediction with Multi-Range Transformers", NeurIPS, 2021. paper arxiv code
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Datasets
Metrics
Bibtex
@InProceedings{Wang_2021_NeurIPS,
author = "Wang, Jiashun and Xu, Huazhe and Narasimhan, Medhini and Wang, Xiaolong",
booktitle = "NeurIPS",
title = "Multi-Person {3D} Motion Prediction with Multi-Range Transformers",
year = "2021"
}
Cui et al., "Towards Accurate 3D Human Motion Prediction From Incomplete Observations", CVPR, 2021. paper
Aliakbarian et al., "Contextually Plausible and Diverse 3D Human Motion Prediction", ICCV, 2021. paper arxiv
-
Datasets
Metrics
Bibtex
@InProceedings{Aliakbarian_2021_ICCV,
author = "Aliakbarian, Sadegh and Saleh, Fatemeh and Petersson, Lars and Gould, Stephen and Salzmann, Mathieu",
title = "Contextually Plausible and Diverse {3D} Human Motion Prediction",
booktitle = "ICCV",
year = "2021"
}
Dang et al., "MSR-GCN: Multi-Scale Residual Graph Convolution Networks for Human Motion Prediction", ICCV, 2021. paper code
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Datasets
Metrics
Bibtex
@InProceedings{Dang_2021_ICCV,
author = "Dang, Lingwei and Nie, Yongwei and Long, Chengjiang and Zhang, Qing and Li, Guiqing",
title = "{MSR-GCN}: Multi-Scale Residual Graph Convolution Networks for Human Motion Prediction",
booktitle = "ICCV",
year = "2021"
}
Liu et al., "Motion Prediction Using Trajectory Cues", ICCV, 2021. paper code
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Datasets
Metrics
Bibtex
@InProceedings{Liu_2021_ICCV,
author = "Liu, Zhenguang and Su, Pengxiang and Wu, Shuang and Shen, Xuanjing and Chen, Haipeng and Hao, Yanbin and Wang, Meng",
title = "Motion Prediction Using Trajectory Cues",
booktitle = "ICCV",
year = "2021"
}
Li et al., "Directed Acyclic Graph Neural Network for Human Motion Prediction", ICRA, 2021. paper code
Zhang et al., "Non-local Graph Convolutional Network for Joint Activity Recognition and Motion Prediction", IROS, 2021. paper arxiv
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Datasets
Metrics
Bibtex
@InProceedings{Zhang_2021_IROS,
author = "Zhang, Dianhao and Vien, Ngo Anh and Van, Mien and McLoone, Seán",
booktitle = "IROS",
title = "Non-local Graph Convolutional Network for Joint Activity Recognition and Motion Prediction",
year = "2021"
}
Aliakbarian et al., "A Stochastic Conditioning Scheme for Diverse Human Motion Prediction", CVPR, 2020. paper code
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Datasets
Metrics
Bibtex
@InProceedings{Aliakbarian_2020_CVPR,
author = "Aliakbarian, Sadegh and Saleh, Fatemeh Sadat and Salzmann, Mathieu and Petersson, Lars and Gould, Stephen",
title = "A Stochastic Conditioning Scheme for Diverse Human Motion Prediction",
booktitle = "CVPR",
year = "2020"
}
Li et al., "Dynamic Multiscale Graph Neural Networks for 3D Skeleton Based Human Motion Prediction", CVPR, 2020. paper arxiv code
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Datasets
Metrics
Bibtex
@InProceedings{Li_2020_CVPR,
author = "Li, Maosen and Chen, Siheng and Zhao, Yangheng and Zhang, Ya and Wang, Yanfeng and Tian, Qi",
title = "Dynamic Multiscale Graph Neural Networks for {3D} Skeleton Based Human Motion Prediction",
booktitle = "CVPR",
year = "2020"
}
Cai et al., "Learning Progressive Joint Propagation for Human Motion Prediction", ECCV, 2020. paper
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Datasets
Metrics
Bibtex
@InProceedings{Cai_2020_ECCV,
author = "Cai, Yujun and Huang, Lin and Wang, Yiwei and Cham, Tat-Jen and Cai, Jianfei and Yuan, Junsong and Liu, Jun and Yang, Xu and Zhu, Yiheng and Shen, Xiaohui and Liu, Ding and Liu, Jing and Thalmann, Nadia M",
title = "Learning Progressive Joint Propagation for Human Motion Prediction",
booktitle = "ECCV",
year = "2020"
}
Chao et al., "Adversarial Refinement Network for Human Motion Prediction", ACCV, 2020. paper arxiv code
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Datasets
Metrics
Bibtex
@InProceedings{Chao_2020_ACCV,
author = "Chao, Xianjin and Bin, Yanrui and Chu, Wenqing and Cao, Xuan and Ge, Yanhao and Wang, Chengjie and Li, Jilin and Huang, Feiyue and Leung, Howard",
title = "Adversarial Refinement Network for Human Motion Prediction",
booktitle = "ACCV",
year = "2020"
}
Bibtex
@Misc{CMU_Mocap_2016,
author = "CMU",
title = "{CMU} Graphics Lab Motion Capture Database",
howpublished = "http://mocap.cs.cmu.edu/",
year = "2016"
}
Cityscapes link paper arxiv
Used in papers
Zhang et al., "ExtDM: Distribution Extrapolation Diffusion Model for Video Prediction", CVPR, 2024. paper code
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Datasets
Metrics
Bibtex
@InProceedings{Zhang_ExtDM_2024_CVPR,
author = "Zhang, Zhicheng and Hu, Junyao and Cheng, Wentao and Paudel, Danda and Yang, Jufeng",
title = "ExtDM: Distribution Extrapolation Diffusion Model for Video Prediction",
booktitle = "CVPR",
year = "2024"
}
Hu et al., "A Dynamic Multi-Scale Voxel Flow Network for Video Prediction", CVPR, 2023. paper arxiv code
-
Datasets
Metrics
Bibtex
@InProceedings{Hu_2023_CVPR,
author = "Hu, Xiaotao and Huang, Zhewei and Huang, Ailin and Xu, Jun and Zhou, Shuchang",
title = "A Dynamic Multi-Scale Voxel Flow Network for Video Prediction",
booktitle = "CVPR",
year = "2023"
}
Geng et al., "Comparing Correspondences: Video Prediction With Correspondence-Wise Losses", CVPR, 2022. paper arxiv code
-
Datasets
Metrics
Bibtex
@InProceedings{Geng_2022_CVPR,
author = "Geng, Daniel and Hamilton, Max and Owens, Andrew",
title = "Comparing Correspondences: Video Prediction With Correspondence-Wise Losses",
booktitle = "CVPR",
year = "2022"
}
Wu et al., "Optimizing Video Prediction via Video Frame Interpolation", CVPR, 2022. paper
-
Datasets
Metrics
Bibtex
@InProceedings{Wu_2022_CVPR,
author = "Wu, Yue and Wen, Qiang and Chen, Qifeng",
title = "Optimizing Video Prediction via Video Frame Interpolation",
booktitle = "CVPR",
year = "2022"
}
Lee et al., "Revisiting Hierarchical Approach for Persistent Long-Term Video Prediction", ICLR, 2021. paper arxiv code
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Datasets
Metrics
Bibtex
@InProceedings{Wonkwang_2021_ICLR,
author = "Lee, Wonkwang and Jung, Whie and Zhang, Han and Chen, Ting and Koh, Jing Yu and Huang, Thomas and Yoon, Hyungsuk and Lee, Honglak and Hong, Seunghoon",
booktitle = "ICLR",
title = "Revisiting Hierarchical Approach for Persistent Long-Term Video Prediction",
year = "2021"
}
Bei et al., "Learning Semantic-Aware Dynamics for Video Prediction", CVPR, 2021. paper arxiv
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Datasets
Metrics
Bibtex
@InProceedings{Bei_2021_CVPR,
author = "Bei, Xinzhu and Yang, Yanchao and Soatto, Stefano",
title = "Learning Semantic-Aware Dynamics for Video Prediction",
booktitle = "CVPR",
year = "2021"
}
Wu et al., "Future Video Synthesis With Object Motion Prediction", CVPR, 2020. paper arxiv
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Datasets
Metrics
Bibtex
@InProceedings{Wu_2020_CVPR,
author = "Wu, Yue and Gao, Rongrong and Park, Jaesik and Chen, Qifeng",
title = "Future Video Synthesis With Object Motion Prediction",
booktitle = "CVPR",
year = "2020"
}
Xu et al., "Structure Preserving Video Prediction", CVPR, 2018. paper
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Datasets
Metrics
Bibtex
@InProceedings{Xu_2018_CVPR,
author = "Xu, Jingwei and Ni, Bingbing and Li, Zefan and Cheng, Shuo and Yang, Xiaokang",
title = "Structure Preserving Video Prediction",
booktitle = "CVPR",
year = "2018"
}
Marchetti et al., "MANTRA: Memory Augmented Networks for Multiple Trajectory Prediction", CVPR, 2020. paper arxiv
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Datasets
Metrics
Bibtex
@InProceedings{Marchetti_2020_CVPR,
author = "Marchetti, Francesco and Becattini, Federico and Seidenari, Lorenzo and Del Bimbo, Alberto",
title = "{MANTRA}: Memory Augmented Networks for Multiple Trajectory Prediction",
booktitle = "CVPR",
year = "2020"
}
Srikanth et al., "INFER: INtermediate Representations For FuturE PRediction", IROS, 2019. paper arxiv code
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Datasets
Metrics
Bibtex
@InProceedings{Srikanth_2019_IROS,
author = "Srikanth, Shashank and Ansari, Junaid Ahmed and Sharma, Sarthak and others",
booktitle = "IROS",
title = "{INFER}: {IN}termediate Representations For {F}utur{E} P{R}ediction",
year = "2019"
}
Graber et al., "Joint Forecasting of Panoptic Segmentations With Difference Attention", CVPR, 2022. paper arxiv code
-
Datasets
Metrics
Bibtex
@InProceedings{Graber_2022_CVPR,
author = "Graber, Colin and Jazra, Cyril and Luo, Wenjie and Gui, Liangyan and Schwing, Alexander G.",
title = "Joint Forecasting of Panoptic Segmentations With Difference Attention",
booktitle = "CVPR",
year = "2022"
}
Lin et al., "Predictive Feature Learning for Future Segmentation Prediction", ICCV, 2021. paper
Saric et al., "Warp to the Future: Joint Forecasting of Features and Feature Motion", CVPR, 2020. paper
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Datasets
Metrics
Bibtex
@InProceedings{Saric_2020_CVPR,
author = "Saric, Josip and Orsic, Marin and Antunovic, Tonci and Vrazic, Sacha and Segvic, Sinisa",
title = "Warp to the Future: Joint Forecasting of Features and Feature Motion",
booktitle = "CVPR",
year = "2020"
}
Hu et al., "Probabilistic Future Prediction for Video Scene Understanding", ECCV, 2020. paper arxiv
-
Datasets
Bibtex
@InProceedings{Hu_2020_ECCV,
author = "Hu, Anthony and Cotter, Fergal and Mohan, Nikhil and Gurau, Corina and Kendall, Alex",
title = "Probabilistic Future Prediction for Video Scene Understanding",
booktitle = "ECCV",
year = "2020"
}
Terwilliger et al., "Recurrent Flow-Guided Semantic Forecasting", WACV, 2019. paper arxiv
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Datasets
Metrics
Bibtex
@InProceedings{Terwilliger_2019_WACV,
author = "Terwilliger, A. and Brazil, G. and Liu, X.",
booktitle = "WACV",
title = "Recurrent Flow-Guided Semantic Forecasting",
year = "2019"
}
Luc et al., "Predicting Future Instance Segmentation By Forecasting Convolutional Features", ECCV, 2018. paper arxiv
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Datasets
Metrics
Bibtex
@InProceedings{Luc_2018_ECCV,
author = "Luc, Pauline and Couprie, Camille and LeCun, Yann and Verbeek, Jakob",
title = "Predicting Future Instance Segmentation By Forecasting Convolutional Features",
booktitle = "ECCV",
year = "2018"
}
Luc et al., "Predicting Deeper Into The Future Of Semantic Segmentation", ICCV, 2017. paper arxiv code
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Datasets
Metrics
Bibtex
@InProceedings{Luc_2017_ICCV,
author = "Luc, Pauline and Neverova, Natalia and Couprie, Camille and Verbeek, Jakob and LeCun, Yann",
title = "Predicting Deeper Into The Future Of Semantic Segmentation",
booktitle = "ICCV",
year = "2017"
}
Jin et al., "Predicting Scene Parsing And Motion Dynamics In The Future", NeurIPS, 2017. paper arxiv
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Datasets
Metrics
Bibtex
@InProceedings{Jin_2017_NeurIPS,
author = "Jin, Xiaojie and Xiao, Huaxin and Shen, Xiaohui and Yang, Jimei and Lin, Zhe and Chen, Yunpeng and Jie, Zequn and Feng, Jiashi and Yan, Shuicheng",
title = "Predicting Scene Parsing And Motion Dynamics In The Future",
booktitle = "NeurIPS",
year = "2017"
}
Bibtex
@InProceedings{Cordts_2016_CVPR,
author = "Cordts, Marius and Omran, Mohamed and Ramos, Sebastian and Rehfeld, Timo and Enzweiler, Markus and Benenson, Rodrigo and Franke, Uwe and Roth, Stefan and Schiele, Bernt",
title = "The Cityscapes Dataset For Semantic Urban Scene Understanding",
booktitle = "CVPR",
year = "2016"
}
NBA link
Used in papers
Wong et al., "SocialCircle: Learning the Angle-based Social Interaction Representation for Pedestrian Trajectory Prediction", CVPR, 2024. paper arxiv code
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Datasets
Metrics
Bibtex
@InProceedings{Wong_SocialCircle_2024_CVPR,
author = "Wong, Conghao and Xia, Beihao and Zou, Ziqian and Wang, Yulong and You, Xinge",
title = "SocialCircle: Learning the Angle-based Social Interaction Representation for Pedestrian Trajectory Prediction",
booktitle = "CVPR",
year = "2024"
}
chib et al., "Enhancing Trajectory Prediction through Self-Supervised Waypoint Distortion Prediction", ICML, 2024. paper arxiv
Dax et al., "Disentangled Neural Relational Inference for Interpretable Motion Prediction", RAL, 2024. paper arxiv
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Datasets
Metrics
Bibtex
@ARTICLE{Dax_Disentangled_2024_RAL,
author = "Dax, Victoria M. and Li, Jiachen and Sachdeva, Enna and Agarwal, Nakul and Kochenderfer, Mykel J.",
journal = "RAL",
title = "Disentangled Neural Relational Inference for Interpretable Motion Prediction",
year = "2024",
volume = "9",
number = "2",
pages = "1452-1459",
keywords = "Predictive models;Trajectory;Vehicle dynamics;Decoding;Data models;Computational modeling;Training;AI-Based Methods;Behavior-Based Systems;Probabilistic Inference",
doi = "10.1109/LRA.2023.3342554"
}
Mao et al., "Leapfrog Diffusion Model for Stochastic Trajectory Prediction", CVPR, 2023. paper arxiv code
Xu et al., "EqMotion: Equivariant Multi-Agent Motion Prediction With Invariant Interaction Reasoning", CVPR, 2023. paper arxiv
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Datasets
Metrics
Bibtex
@InProceedings{Xu_2023_CVPR_1,
author = "Xu, Chenxin and Tan, Robby T. and Tan, Yuhong and Chen, Siheng and Wang, Yu Guang and Wang, Xinchao and Wang, Yanfeng",
title = "EqMotion: Equivariant Multi-Agent Motion Prediction With Invariant Interaction Reasoning",
booktitle = "CVPR",
year = "2023"
}
Sun et al., "Stimulus Verification Is a Universal and Effective Sampler in Multi-Modal Human Trajectory Prediction", CVPR, 2023. paper
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Datasets
Metrics
Bibtex
@InProceedings{Sun_2023_CVPR_2,
author = "Sun, Jianhua and Li, Yuxuan and Chai, Liang and Lu, Cewu",
title = "Stimulus Verification Is a Universal and Effective Sampler in Multi-Modal Human Trajectory Prediction",
booktitle = "CVPR",
year = "2023"
}
Xu et al., "Remember Intentions: Retrospective-Memory-Based Trajectory Prediction", CVPR, 2022. paper arxiv code
Xu et al., "GroupNet: Multiscale Hypergraph Neural Networks for Trajectory Prediction With Relational Reasoning", CVPR, 2022. paper arxiv code
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Datasets
Metrics
Bibtex
@InProceedings{Xu_2022_CVPR_2,
author = "Xu, Chenxin and Li, Maosen and Ni, Zhenyang and Zhang, Ya and Chen, Siheng",
title = "{GroupNet}: Multiscale Hypergraph Neural Networks for Trajectory Prediction With Relational Reasoning",
booktitle = "CVPR",
year = "2022"
}
Hu et al., "Entry-Flipped Transformer for Inference and Prediction of Participant Behavior", ECCV, 2022. paper arxiv
Xu et al., "SocialVAE: Human Trajectory Prediction Using Timewise Latents", ECCV, 2022. paper arxiv code
Fassmeyer et al., "Semi-Supervised Generative Models for Multiagent Trajectories", NeurIPS, 2022. paper code
Makansi et al., "You Mostly Walk Alone: Analyzing Feature Attribution in Trajectory Prediction", ICLR, 2022. paper arxiv
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Datasets
Metrics
Bibtex
@InProceedings{Makansi_2022_ICLR,
author = "Makansi, Osama and Kugelgen, Julius Von and Locatello, Francesco and Gehler, Peter Vincent and Janzing, Dominik and Brox, Thomas and Scholkopf, Bernhard",
title = "You Mostly Walk Alone: Analyzing Feature Attribution in Trajectory Prediction",
booktitle = "ICLR",
year = "2022"
}
Navarro et al., "Social-PatteRNN: Socially-Aware Trajectory Prediction Guided by Motion Patterns", IROS, 2022. paper arxiv
Li et al., "GRIN: Generative Relation and Intention Network for Multi-agent Trajectory Prediction", NeurIPS, 2021. paper
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Datasets
Metrics
Bibtex
@InProceedings{Li_2021_NeurIPS,
author = "Li, Longyuan and Yao, Jian and Wenliang, Li and He, Tong and Xiao, Tianjun and Yan, Junchi and Wipf, David and Zhang, Zheng",
booktitle = "NeurIPS",
title = "{GRIN}: Generative Relation and Intention Network for Multi-agent Trajectory Prediction",
year = "2021"
}
Kamra et al., "Multi-agent Trajectory Prediction with Fuzzy Query Attention", NeurIPS, 2020. paper arxiv code
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Datasets
Metrics
Bibtex
@InProceedings{Kamra_2020_NeurIPS,
author = "Kamra, Nitin and Zhu, Hao and Trivedi, Dweep Kumarbhai and Zhang, Ming and Liu, Yan",
editor = "Larochelle, H. and Ranzato, M. and Hadsell, R. and Balcan, M. F. and Lin, H.",
booktitle = "NeurIPS",
title = "Multi-agent Trajectory Prediction with Fuzzy Query Attention",
year = "2020"
}
Li et al., "EvolveGraph: Multi-Agent Trajectory Prediction with Dynamic Relational Reasoning", NeurIPS, 2020. paper arxiv
Bibtex
@Misc{Linou_2016,
author = "Luo, K",
Title = "{NBA}-Player-Movements",
HowPublished = "Online",
year = "2016",
url = "https://github.com/linouk23/NBA-Player-Movements"
}
NTU RGB-D link paper arxiv
Used in papers
Rupprecht et al., "Learning in an Uncertain World: Representing Ambiguity Through Multiple Hypotheses", ICCV, 2017. paper arxiv
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Datasets
Bibtex
@InProceedings{Rupprecht_2017_ICCV,
author = "Rupprecht, Christian and Laina, Iro and DiPietro, Robert and Baust, Maximilian and Tombari, Federico and Navab, Nassir and Hager, Gregory D",
title = "Learning in an Uncertain World: Representing Ambiguity Through Multiple Hypotheses",
booktitle = "ICCV",
year = "2017"
}
Stergiou et al., "The Wisdom of Crowds: Temporal Progressive Attention for Early Action Prediction", CVPR, 2023. paper arxiv code
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Datasets
Metrics
Bibtex
@InProceedings{Stergiou_2023_CVPR,
author = "Stergiou, Alexandros and Damen, Dima",
title = "The Wisdom of Crowds: Temporal Progressive Attention for Early Action Prediction",
booktitle = "CVPR",
year = "2023"
}
Foo et al., "ERA: Expert Retrieval and Assembly for Early Action Prediction", ECCV, 2022. paper arxiv
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Datasets
Metrics
Bibtex
@InProceedings{Foo_2022_ECCV,
author = "Foo, Lin Geng and Li, Tianjiao and Rahmani, Hossein and Ke, Qiuhong and Liu, Jun",
title = "{ERA}: Expert Retrieval and Assembly for Early Action Prediction",
booktitle = "ECCV",
year = "2022"
}
Li et al., "HARD-Net: Hardness-AwaRe Discrimination Network for 3D Early Activity Prediction", ECCV, 2020. paper
Wang et al., "Progressive Teacher-Student Learning For Early Action Prediction", CVPR, 2019. paper
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Datasets
Metrics
Bibtex
@InProceedings{Wang_2019_CVPR,
author = "Wang, Xionghui and Hu, Jian-Fang and Lai, Jian-Huang and Zhang, Jianguo and Zheng, Wei-Shi",
title = "Progressive Teacher-Student Learning For Early Action Prediction",
booktitle = "CVPR",
year = "2019"
}
Mao et al., "Masked Motion Predictors are Strong 3D Action Representation Learners", ICCV, 2023. paper arxiv code
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Datasets
Metrics
Bibtex
@InProceedings{Mao_2023_ICCV,
author = "Mao, Yunyao and Deng, Jiajun and Zhou, Wengang and Fang, Yao and Ouyang, Wanli and Li, Houqiang",
title = "Masked Motion Predictors are Strong 3D Action Representation Learners",
booktitle = "ICCV",
year = "2023"
}
Yasar et al., "VADER: Vector-Quantized Generative Adversarial Network for Motion Prediction", IROS, 2023. paper
Mao et al., "Weakly-Supervised Action Transition Learning for Stochastic Human Motion Prediction", CVPR, 2022. paper code
Zhang et al., "Non-local Graph Convolutional Network for Joint Activity Recognition and Motion Prediction", IROS, 2021. paper arxiv
-
Datasets
Metrics
Bibtex
@InProceedings{Zhang_2021_IROS,
author = "Zhang, Dianhao and Vien, Ngo Anh and Van, Mien and McLoone, Seán",
booktitle = "IROS",
title = "Non-local Graph Convolutional Network for Joint Activity Recognition and Motion Prediction",
year = "2021"
}
Yasar et al., "A Scalable Approach to Predict Multi-Agent Motion for Human-Robot Collaboration", RAL, 2021. paper
-
Datasets
Metrics
Bibtex
@Article{Yasar_2021_RAL,
author = "Yasar, Mohammad Samin and Iqbal, Tariq",
journal = "RAL",
title = "A Scalable Approach to Predict Multi-Agent Motion for Human-Robot Collaboration",
year = "2021",
volume = "6",
number = "2",
pages = "1686-1693"
}
Adeli et al., "Socially and Contextually Aware Human Motion and Pose Forecasting", RAL, 2020. paper arxiv
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Datasets
Metrics
Bibtex
@Article{Adeli_2020_RAL,
author = "Adeli, V. and Adeli, E. and Reid, I. and Niebles, J. C. and Rezatofighi, H.",
journal = "RAL",
title = "Socially and Contextually Aware Human Motion and Pose Forecasting",
year = "2020",
volume = "5",
number = "4",
pages = "6033-6040"
}
Bibtex
@InProceedings{Shahroudy_2016_CVPR,
author = "Shahroudy, Amir and Liu, Jun and Ng, Tian-Tsong and Wang, Gang",
title = "{NTU RGB+D}: A Large Scale Dataset For 3D Human Activity Analysis",
booktitle = "CVPR",
year = "2016"
}
BAIR Push link paper arxiv
Used in papers
Shrivastava et al., "Video Prediction by Modeling Videos as Continuous Multi-Dimensional Processes", CVPR, 2024. paper
Zhang et al., "ExtDM: Distribution Extrapolation Diffusion Model for Video Prediction", CVPR, 2024. paper code
-
Datasets
Metrics
Bibtex
@InProceedings{Zhang_ExtDM_2024_CVPR,
author = "Zhang, Zhicheng and Hu, Junyao and Cheng, Wentao and Paudel, Danda and Yang, Jufeng",
title = "ExtDM: Distribution Extrapolation Diffusion Model for Video Prediction",
booktitle = "CVPR",
year = "2024"
}
Davtyan et al., "Efficient Video Prediction via Sparsely Conditioned Flow Matching", ICCV, 2023. paper arxiv code
Chatterjee et al., "A Hierarchical Variational Neural Uncertainty Model for Stochastic Video Prediction", ICCV, 2021. paper
-
Datasets
Metrics
Bibtex
@InProceedings{Chatterjee_2021_ICCV,
author = "Chatterjee, Moitreya and Ahuja, Narendra and Cherian, Anoop",
title = "A Hierarchical Variational Neural Uncertainty Model for Stochastic Video Prediction",
booktitle = "ICCV",
year = "2021"
}
Jin et al., "Exploring Spatial-Temporal Multi-Frequency Analysis for High-Fidelity and Temporal-Consistency Video Prediction", CVPR, 2020. paper arxiv code
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Datasets
Metrics
Bibtex
@InProceedings{Jin_2020_CVPR,
author = "Jin, Beibei and Hu, Yu and Tang, Qiankun and Niu, Jingyu and Shi, Zhiping and Han, Yinhe and Li, Xiaowei",
title = "Exploring Spatial-Temporal Multi-Frequency Analysis for High-Fidelity and Temporal-Consistency Video Prediction",
booktitle = "CVPR",
year = "2020"
}
Franceschi et al., "Stochastic Latent Residual Video Prediction", ICML, 2020. paper arxiv code
-
Datasets
Metrics
Bibtex
@InProceedings{Franceschi_2020_ICML,
author = {Franceschi, Jean-Yves and Delasalles, Edouard and Chen, Micka{\"e}l and Lamprier, Sylvain and Gallinari, Patrick},
title = "Stochastic Latent Residual Video Prediction",
booktitle = "ICML",
year = "2020"
}
Bibtex
@InProceedings{Finn_2016_NeurIPS,
author = "Finn, Chelsea and Goodfellow, Ian and Levine, Sergey",
title = "Unsupervised Learning For Physical Interaction Through Video Prediction",
booktitle = "NeurIPS",
year = "2016"
}
Visual Storytelling (VIST) link paper
Used in papers
Bibtex
@InProceedings{Huang_2016_NAACL,
author = "Huang, Ting-Hao K. and Ferraro, Francis and Mostafazadeh, Nasrin and Misra, Ishan and Devlin, Jacob and Agrawal, Aishwarya and Girshick, Ross and He, Xiaodong and Kohli, Pushmeet and Batra, Dhruv and others",
title = "Visual Storytelling",
booktitle = "NAACL",
year = "2016"
}
The Cancer Genome Atlas Program (TCGA) link paper
Used in papers
Song et al., "Multimodal Prototyping for cancer survival prediction", ICML, 2024. paper arxiv code
-
Datasets
Metrics
Bibtex
@inproceedings{Song_Multimodal_2024_ICML,
author = "Song, Andrew H. and Chen, Richard J. and Jaume, Guillaume and Vaidya, Anurag Jayant and Baras, Alexander and Mahmood, Faisal",
title = "Multimodal Prototyping for cancer survival prediction",
booktitle = "ICML",
year = "2024"
}
Zhang et al., "Prototypical Information Bottlenecking and Disentangling for Multimodal Cancer Survival Prediction", ICLR, 2024. paper arxiv code
-
Datasets
Metrics
Bibtex
@inproceedings{Zhang_prototypical_2024_ICLR,
author = "Zhang, Yilan and Xu, Yingxue and Chen, Jianqi and Xie, Fengying and Chen, Hao",
title = "Prototypical Information Bottlenecking and Disentangling for Multimodal Cancer Survival Prediction",
booktitle = "ICLR",
year = "2024"
}
Bibtex
@article{Wang_practical_2024_SGMP,
author = "Wang, Zhining and Jensen, Mark A and Zenklusen, Jean Claude",
title = "A practical guide to the cancer genome atlas (TCGA)",
journal = "Statistical Genomics: Methods and Protocols",
pages = "111--141",
year = "2016"
}
TV Series link paper arxiv
Used in papers
Gao et al., "RED: Reinforced Encoder-Decoder Networks For Action Anticipation", BMVC, 2017. paper arxiv
-
Datasets
Metrics
Bibtex
@InProceedings{Gao_2017_BMVC,
author = "Gao, Jiyang and Yang, Zhenheng and Nevatia, Ram",
title = "{RED}: Reinforced Encoder-Decoder Networks For Action Anticipation",
year = "2017",
booktitle = "BMVC"
}
Bibtex
@InProceedings{De_2016_ECCV,
author = "De Geest, Roeland and Gavves, Efstratios and Ghodrati, Amir and Li, Zhenyang and Snoek, Cees and Tuytelaars, Tinne",
title = "Online Action Detection",
booktitle = "ECCV",
year = "2016"
}
Online Action Detection (OAD) link paper arxiv
Used in papers
Liu et al., "SSNet: Scale Selection Network For Online 3D Action Prediction", CVPR, 2018. paper
Bibtex
@Article{Li_2016_ECCV,
author = "Li, Yanghao and Lan, Cuiling and Xing, Junliang and Zeng, Wenjun and Yuan, Chunfeng and Liu, Jiaying",
title = "Online Human Action Detection Using Joint Classification-Regression Recurrent Neural Networks",
journal = "ECCV",
year = "2016"
}
Ongoing Activity (OA) link paper
Used in papers
Li et al., "Recognition Of Ongoing Complex Activities By Sequence Prediction Over A Hierarchical Label Space", WACV, 2016. paper
Bibtex
@InProceedings{Li_2016_WACV,
author = "Li, W. and Fritz, M.",
booktitle = "WACV",
title = "Recognition Of Ongoing Complex Activities By Sequence Prediction Over A Hierarchical Label Space",
year = "2016"
}
Youtube-8M link arxiv
Used in papers
Reda et al., "SDC-Net: Video Prediction Using Spatially-Displaced Convolution", ECCV, 2018. paper arxiv
-
Datasets
Metrics
Bibtex
@InProceedings{Reda_2018_ECCV,
author = "Reda, Fitsum A. and Liu, Guilin and Shih, Kevin J. and Kirby, Robert and Barker, Jon and Tarjan, David and Tao, Andrew and Catanzaro, Bryan",
title = "{SDC-Net}: Video Prediction Using Spatially-Displaced Convolution",
booktitle = "ECCV",
year = "2018"
}
Bibtex
@Article{Abu_2016_arxiv,
author = "Abu-El-Haija, Sami and Kothari, Nisarg and Lee, Joonseok and Natsev, Paul and Toderici, George and Varadarajan, Balakrishnan and Vijayanarasimhan, Sudheendra",
title = "{YouTube-8M}: A Large-Scale Video Classification Benchmark",
journal = "arXiv:1609.08675",
year = "2016"
}
Miss Universe (MU) link paper arxiv
Used in papers
Bibtex
@InProceedings{Carvajal_2016_ICPR,
author = "Carvajal, J. and Wiliem, A. and Sanderson, C. and Lovell, B.",
booktitle = "ICPR",
title = "Towards Miss Universe Automatic Prediction: The Evening Gown Competition",
year = "2016"
}
Bouncing Ball (BB) link paper arxiv
Used in papers
Hsieh et al., "Learning To Decompose And Disentangle Representations For Video Prediction", NeurIPS, 2018. paper arxiv code
-
Datasets
Metrics
Bibtex
@InProceedings{Hsieh_2018_NeurIPS,
author = "Hsieh, Jun-Ting and Liu, Bingbin and Huang, De-An and Fei-Fei, Li F and Niebles, Juan Carlos",
title = "Learning To Decompose And Disentangle Representations For Video Prediction",
booktitle = "NeurIPS",
year = "2018"
}
Bibtex
@Article{Chang_2016_arxiv,
author = "Chang, Michael B and Ullman, Tomer and Torralba, Antonio and Tenenbaum, Joshua B",
title = "A Compositional Object-Based Approach To Learning Physical Dynamics",
journal = "arXiv:1612.00341",
year = "2016"
}
Charades link paper arxiv
Used in papers
Piergiovanni et al., "Adversarial Generative Grammars for Human Activity Prediction", ECCV, 2020. paper arxiv
-
Datasets
Metrics
Bibtex
@InProceedings{Piergiovanni_2020_ECCV,
author = "Piergiovanni, AJ and Angelova, Anelia and Toshev, Alexander and Ryoo, Michael S",
title = "Adversarial Generative Grammars for Human Activity Prediction",
booktitle = "ECCV",
year = "2020"
}
Bibtex
@InProceedings{Sigurdsson_2016_ECCV,
author = {Sigurdsson, Gunnar A and Varol, G{\"u}l and Wang, Xiaolong and Farhadi, Ali and Laptev, Ivan and Gupta, Abhinav},
title = "Hollywood in Homes: Crowdsourcing Data Collection for Activity Understanding",
booktitle = "ECCV",
year = "2016"
}
Volleyball link paper arxiv
Used in papers
Chen et al., "Group Activity Prediction with Sequential Relational Anticipation Model", ECCV, 2020. paper arxiv
-
Datasets
Metrics
Bibtex
@InProceedings{Chen_2020_ECCV,
author = "Chen, Junwen and Bao, Wentao and Kong, Yu",
title = "Group Activity Prediction with Sequential Relational Anticipation Model",
booktitle = "ECCV",
year = "2020"
}
Bibtex
@InProceedings{Ibrahim_2016_CVPR,
author = "Ibrahim, Mostafa S and Muralidharan, Srikanth and Deng, Zhiwei and Vahdat, Arash and Mori, Greg",
title = "A Hierarchical Deep Temporal Model for Group Activity Recognition",
booktitle = "CVPR",
year = "2016"
}
Ceilidh Dance link paper
Used in papers
Hu et al., "Entry-Flipped Transformer for Inference and Prediction of Participant Behavior", ECCV, 2022. paper arxiv
-
Datasets
Bibtex
@InProceedings{Hu_2022_ECCV,
author = "Hu, Bo and Cham, Tat-Jen",
title = "Entry-Flipped Transformer for Inference and Prediction of Participant Behavior",
booktitle = "ECCV",
year = "2022"
}
Bibtex
@mastersthesis{Aizeboje_2016_masc,
author = "Aizeboje, Jeremiah",
title = "Ceilidh Dance Recognition from an Overhead Camera",
year = "2016",
school = "University of Edinburgh"
}
FlyingThings3D link paper arxiv
Used in papers
Dong et al., "MemFlow: Optical Flow Estimation and Prediction with Memory", CVPR, 2024. paper arxiv
-
Datasets
Metrics
Bibtex
@InProceedings{Dong_MemFlow_2024_CVPR,
author = "Dong, Qiaole and Fu, Yanwei",
title = "MemFlow: Optical Flow Estimation and Prediction with Memory",
booktitle = "CVPR",
year = "2024"
}
Bibtex
@InProceedings{Mayer_Large_2016_CVPR,
author = "Mayer, Nikolaus and Ilg, Eddy and Hausser, Philip and Fischer, Philipp and Cremers, Daniel and Dosovitskiy, Alexey and Brox, Thomas",
title = "A Large Dataset to Train Convolutional Networks for Disparity, Optical Flow, and Scene Flow Estimation",
booktitle = "CVPR",
year = "2016"
}
KIT Whole-Body Human Motion (KIT WBHM) link paper
Used in papers
Lee, "Commonsense Spatial Knowledge-aware 3-D Human Motion and Object Interaction Prediction", ICRA, 2024. paper
Bibtex
@ARTICLE{Mandery_Unifying_2016_ToR,
author = {Mandery, Christian and Terlemez, \"Omer and Do, Martin and Vahrenkamp, Nikolaus and Asfour, Tamim},
title = "Unifying Representations and Large-Scale Whole-Body Motion Databases for Studying Human Motion",
pages = "796--809",
volume = "32",
number = "4",
journal = "IEEE Transactions on Robotics",
year = "2016"
}
- Summary: A dataset of moving digits on a simple uniform background
- Applications: Video prediction
- Data type and annotations: Grayscale
- Task: Digit
- Summary: A dataset of 20K+ videos of 101 diverse action classes
- Applications: Video prediction, Action prediction
- Data type and annotations: RGB, activity label, temporal segment
- Task: Activity
- Summary: A collection of videos from existing datasets for the purpose of object tracking
- Applications: Trajectory prediction
- Data type and annotations: RGB, bounding box
- Task: Surveillance
- Summary: A dataset of 700 driving events using inside and outside looking cameras with annotated actions for various driving maneuvers
- Applications: Action prediction
- Data type and annotations: RGB, bounding box, attribute, temporal segment, vehicle sensors
- Task: Driving
- Summary: A multiview group activity dataset recorded with 10 RGB-D sensors and 30+ HD views with the corresponding 3D annotations
- Applications: Action prediction, Motion prediction
- Data type and annotations: RGBD, multiview, 3D pose, 3D facial landmark, Transcripts
- Task: Interaction
- Summary: A dataset of 12 simple activities in 480 video clips with depth maps
- Applications: Action prediction
- Data type and annotations: RGBD, 3D pose, activity label
- Task: Object interaction
- Summary: A dataset of 648 hours of video with 100 videos per 200 different activity classes
- Applications: Video prediction
- Data type and annotations: RGB, Activity Label
- Task: Activity
- Summary: A dataset of 27 actions performed by 8 subjects collected using Kinect sensor.
- Applications: Motion prediction
- Data type and annotations: RGB, Depth, 3D pose, Inertial sensor
- Task: Activity
- Summary: A dataset of 458 videos of 21 daily actions in office and kitchen environments recorded using a Kinect V2 sensor
- Applications: Action prediction
- Data type and annotations: RGBD, 3D pose, activity label, temporal segment
- Task: Activity
- Summary: A complex event dataset of 61 event categories in 50K+ images
- Applications: Action prediction
- Data type and annotations: RGB, activity label
- Task: Activity
- Summary: An egocentric dataset of 37 videos of 7 cooking activities recorded from 26 subjects with the corresponding gaze tracking information
- Applications: Action prediction
- Data type and annotations: RGB, gaze, mask, activity label, temporal segment
- Task: Cooking (egocentric)
- Summary: An egocentric dataset of 5 daily activities, such as drinking water, using a fridge, etc., consists of 591 video clips recorded at 30fps
- Applications: Action prediction
- Data type and annotations: RGB, activity label, temporal segment
- Task: Activity (egocentric)
- Summary: A dataset of 10K RGB-D images of indoor environments with the corresponding 2D and 3D annotations
- Applications: Other prediction
- Data type and annotations: RGBD, 3D bounding box, object class
- Task: Place
- Summary: A dataset of 142M+ product reviews from Amazon with corresponding metadata including price, brand, descriptions, category information, etc.
- Applications: Other prediction
- Data type and annotations: Features, attribute, text
- Task: Fashion
- Summary: A human motion dataset consists of 2.4K+ experiments using 224 subjects and 135 objects
- Applications: Motion prediction
- Data type and annotations: RGB, 3D Pose
- Task: Pose
- Summary: The dataset of 12 RGB-D video sequences of a person moving in front of a Kinect in a scene with obstacles
- Applications: Motion prediction
- Data type and annotations: RGBD, 3D Pose
- Task: Activity
- Summary: An activity dataset of 1M images and the content of the corresponding tweets collected in years 2013-14
- Applications: Other prediction
- Data type and annotations: RGB, attribute, text
- Task: Tweet
Moving MNIST (MMNIST) link paper arxiv
Used in papers
Zhang et al., "ExtDM: Distribution Extrapolation Diffusion Model for Video Prediction", CVPR, 2024. paper code
-
Datasets
Metrics
Bibtex
@InProceedings{Zhang_ExtDM_2024_CVPR,
author = "Zhang, Zhicheng and Hu, Junyao and Cheng, Wentao and Paudel, Danda and Yang, Jufeng",
title = "ExtDM: Distribution Extrapolation Diffusion Model for Video Prediction",
booktitle = "CVPR",
year = "2024"
}
Pourheydari et al., "TaylorSwiftNet: Taylor Driven Temporal Modeling for Swift Future Frame Prediction", BMVC, 2022. paper arxiv
-
Datasets
Metrics
Bibtex
@InProceedings{Pourheydari_2022_BMVC,
author = "Pourheydari, Mohammad Saber and Bahrami, Emad and Fayyaz, Mohsen and Francesca, Gianpiero and Noroozi, Mehdi and Gall, Jürgen",
title = "{TaylorSwiftNet}: Taylor Driven Temporal Modeling for Swift Future Frame Prediction",
booktitle = "BMVC",
year = "2022"
}
Villar-Corrales et al., "MSPred: Video Prediction at Multiple Spatio-Temporal Scales with Hierarchical Recurrent Networks", BMVC, 2022. paper arxiv code
-
Datasets
Metrics
Bibtex
@InProceedings{Villar-Corrales_2022_BMVC,
author = "Villar-Corrales, Angel and Karapetyan, Ani and Boltres, Andreas and Behnke, Sven",
title = "{MSPred}: Video Prediction at Multiple Spatio-Temporal Scales with Hierarchical Recurrent Networks",
booktitle = "BMVC",
year = "2022"
}
Wang et al., "Towards Unified Multi-Excitation for Unsupervised Video Prediction", BMVC, 2022. paper code
-
Datasets
Metrics
Bibtex
@InProceedings{Wang_2022_BMVC,
author = "Wang, Junyan and Likun, Qin and Zhang, Peng and Long, Yang and Hu, Bingzhang and Pagnucco, Maurice and Wang, Shizheng and Song, Yang",
title = "Towards Unified Multi-Excitation for Unsupervised Video Prediction",
booktitle = "BMVC",
year = "2022"
}
Ben et al., "PhyLoNet: Physically-Constrained Long Term Video Prediction", ACCV, 2022. paper
Chang et al., "MAU: A Motion-Aware Unit for Video Prediction and Beyond", NeurIPS, 2021. paper
-
Datasets
Metrics
Bibtex
@InProceedings{Chang_2021_NeurIPS,
author = "Chang, Zheng and Zhang, Xinfeng and Wang, Shanshe and Ma, Siwei and Ye, Yan and Xinguang, Xiang and Gao, Wen",
booktitle = "NeurIPS",
title = "{MAU}: A Motion-Aware Unit for Video Prediction and Beyond",
year = "2021"
}
Lee et al., "Video Prediction Recalling Long-Term Motion Context via Memory Alignment Learning", CVPR, 2021. paper arxiv code
-
Datasets
Metrics
Bibtex
@InProceedings{Lee_2021_CVPR,
author = "Lee, Sangmin and Kim, Hak Gu and Choi, Dae Hwi and Kim, Hyung-Il and Ro, Yong Man",
title = "Video Prediction Recalling Long-Term Motion Context via Memory Alignment Learning",
booktitle = "CVPR",
year = "2021"
}
Chatterjee et al., "A Hierarchical Variational Neural Uncertainty Model for Stochastic Video Prediction", ICCV, 2021. paper
-
Datasets
Metrics
Bibtex
@InProceedings{Chatterjee_2021_ICCV,
author = "Chatterjee, Moitreya and Ahuja, Narendra and Cherian, Anoop",
title = "A Hierarchical Variational Neural Uncertainty Model for Stochastic Video Prediction",
booktitle = "ICCV",
year = "2021"
}
Le et al., "Disentangling Physical Dynamics From Unknown Factors for Unsupervised Video Prediction", CVPR, 2020. paper arxiv code
Wang et al., "Probabilistic Video Prediction From Noisy Data With a Posterior Confidence", CVPR, 2020. paper
Franceschi et al., "Stochastic Latent Residual Video Prediction", ICML, 2020. paper arxiv code
-
Datasets
Metrics
Bibtex
@InProceedings{Franceschi_2020_ICML,
author = {Franceschi, Jean-Yves and Delasalles, Edouard and Chen, Micka{\"e}l and Lamprier, Sylvain and Gallinari, Patrick},
title = "Stochastic Latent Residual Video Prediction",
booktitle = "ICML",
year = "2020"
}
Yao et al., "Unsupervised Transfer Learning for Spatiotemporal Predictive Networks", ICML, 2020. paper arxiv code
Lee et al., "Mutual Suppression Network For Video Prediction Using Disentangled Features", BMVC, 2019. paper arxiv
Wang et al., "Order Matters: Shuffling Sequence Generation For Video Prediction", BMVC, 2019. paper arxiv code
Oliu et al., "Folded Recurrent Neural Networks For Future Video Prediction", ECCV, 2018. paper arxiv
Hsieh et al., "Learning To Decompose And Disentangle Representations For Video Prediction", NeurIPS, 2018. paper arxiv code
-
Datasets
Metrics
Bibtex
@InProceedings{Hsieh_2018_NeurIPS,
author = "Hsieh, Jun-Ting and Liu, Bingbin and Huang, De-An and Fei-Fei, Li F and Niebles, Juan Carlos",
title = "Learning To Decompose And Disentangle Representations For Video Prediction",
booktitle = "NeurIPS",
year = "2018"
}
Lu et al., "Flexible Spatio-Temporal Networks For Video Prediction", CVPR, 2017. paper
Zeng et al., "Visual Forecasting By Imitating Dynamics In Natural Sequences", ICCV, 2017. paper arxiv
Wang et al., "PredRNN: Recurrent Neural Networks For Predictive Learning Using Spatiotemporal LSTMs", NeurIPS, 2017. paper code
-
Datasets
Metrics
Bibtex
@InProceedings{Wang_2017_NeurIPS,
author = "Wang, Yunbo and Long, Mingsheng and Wang, Jianmin and Gao, Zhifeng and Yu, Philip S",
title = "{PredRNN}: Recurrent Neural Networks For Predictive Learning Using Spatiotemporal {LSTMs}",
booktitle = "NeurIPS",
year = "2017"
}
Bibtex
@InProceedings{Srivastava_2015_ICML,
author = "Srivastava, Nitish and Mansimov, Elman and Salakhudinov, Ruslan",
title = "Unsupervised Learning Of Video Representations Using {LSTMs}",
booktitle = "ICML",
year = "2015"
}
THUMOS link
Used in papers
Piergiovanni et al., "Adversarial Generative Grammars for Human Activity Prediction", ECCV, 2020. paper arxiv
-
Datasets
Metrics
Bibtex
@InProceedings{Piergiovanni_2020_ECCV,
author = "Piergiovanni, AJ and Angelova, Anelia and Toshev, Alexander and Ryoo, Michael S",
title = "Adversarial Generative Grammars for Human Activity Prediction",
booktitle = "ECCV",
year = "2020"
}
Zhong et al., "Unsupervised Learning For Forecasting Action Representations", ICIP, 2018. paper
-
Datasets
Metrics
Bibtex
@InProceedings{Zhong_2018_ICIP,
author = "Zhong, Y. and Zheng, W.",
booktitle = "ICIP",
title = "Unsupervised Learning For Forecasting Action Representations",
year = "2018"
}
Gao et al., "RED: Reinforced Encoder-Decoder Networks For Action Anticipation", BMVC, 2017. paper arxiv
-
Datasets
Metrics
Bibtex
@InProceedings{Gao_2017_BMVC,
author = "Gao, Jiyang and Yang, Zhenheng and Nevatia, Ram",
title = "{RED}: Reinforced Encoder-Decoder Networks For Action Anticipation",
year = "2017",
booktitle = "BMVC"
}
Vondrick et al., "Anticipating Visual Representations From Unlabeled Video", CVPR, 2016. paper arxiv
-
Datasets
Metrics
Bibtex
@InProceedings{Vondrick_2016_CVPR_2,
author = "Vondrick, Carl and Pirsiavash, Hamed and Torralba, Antonio",
title = "Anticipating Visual Representations From Unlabeled Video",
booktitle = "CVPR",
year = "2016"
}
Bibtex
@Misc{Gorban_2015,
author = "Gorban, A. and Idrees, H. and Jiang, Y.-G. and Roshan Zamir, A. and Laptev, I. and Shah, M. and Sukthankar, R.",
title = "Thumos Challenge: Action Recognition With A Large Number Of Classes",
howpublished = "\url{http://www.thumos.info/}",
Year = "2015"
}
MOT link arxiv
Used in papers
Chen et al., "S2F2: Single-Stage Flow Forecasting for Future Multiple Trajectories Prediction", ECCV, 2022. paper
Dendorfer et al., "Quo Vadis: Is Trajectory Forecasting the Key Towards Long-Term Multi-Object Tracking?", NeurIPS, 2022. paper arxiv code
-
Datasets
Metrics
Bibtex
@InProceedings{Dendorfer_2022_NeurIPS,
author = "Dendorfer, Patrick and Yugay, Vladimir and Osep, Aljosa and Leal-Taix{\'e}, Laura",
title = "{Quo Vadis}: Is Trajectory Forecasting the Key Towards Long-Term Multi-Object Tracking?",
booktitle = "NeurIPS",
year = "2022"
}
Meng et al., "Forecasting Human Trajectory from Scene History", NeurIPS, 2022. paper arxiv code
-
Datasets
Metrics
Bibtex
@InProceedings{Meng_2022_NeurIPS,
author = "Meng, Mancheng and Wu, Ziyan and Chen, Terrence and Cai, Xiran and Zhou, Xiang Sean and Yang, Fan and Shen, Dinggang",
title = "Forecasting Human Trajectory from Scene History",
booktitle = "NeurIPS",
year = "2022"
}
Sanchez-Matilla et al., "A Predictor Of Moving Objects For First-Person Vision", ICIP, 2019. paper
Bibtex
@Article{Leal_2015_arxiv,
author = "Leal-Taix\'e, Laura and Milan, Anton and Reid, Ian and Roth, Stefan and Schindler, Konrad",
title = "Motchallenge 2015: Towards A Benchmark For Multi-Target Tracking",
journal = "arXiv:1504.01942",
year = "2015"
}
Brain4Cars link paper arxiv
Used in papers
Kung et al., "Looking Inside Out: Anticipating Driver Intent From Videos", ICRA, 2024. paper arxiv code
-
Datasets
Metrics
Bibtex
@inproceedings{Kung_looking_2024_ICRA,
author = "Kung, Yung-Chi and Zhang, Arthur and Wang, Junmin and Biswas, Joydeep",
booktitle = "ICRA",
title = "Looking Inside Out: Anticipating Driver Intent From Videos",
year = "2024"
}
Jain et al., "Recurrent Neural Networks For Driver Activity Anticipation Via Sensory-Fusion Architecture", ICRA, 2016. paper arxiv code
-
Datasets
Metrics
Bibtex
@InProceedings{Jain_2016_ICRA,
author = "Jain, A. and Singh, A. and Koppula, H. S. and Soh, S. and Saxena, A.",
booktitle = "ICRA",
title = "Recurrent Neural Networks For Driver Activity Anticipation Via Sensory-Fusion Architecture",
year = "2016"
}
Jain et al., "Car That Knows Before You Do: Anticipating Maneuvers Via Learning Temporal Driving Models", ICCV, 2015. paper arxiv
-
Datasets
Metrics
Bibtex
@InProceedings{Jain_2015_ICCV,
author = "Jain, Ashesh and Koppula, Hema S. and Raghavan, Bharad and Soh, Shane and Saxena, Ashutosh",
title = "Car That Knows Before You Do: Anticipating Maneuvers Via Learning Temporal Driving Models",
booktitle = "ICCV",
year = "2015"
}
Bibtex
@InProceedings{Jain_2015_ICCV,
author = "Jain, Ashesh and Koppula, Hema S. and Raghavan, Bharad and Soh, Shane and Saxena, Ashutosh",
title = "Car That Knows Before You Do: Anticipating Maneuvers Via Learning Temporal Driving Models",
booktitle = "ICCV",
year = "2015"
}
CMU Panoptic link paper arxiv
Used in papers
Joo et al., "Towards Social Artificial Intelligence: Nonverbal Social Signal Prediction In A Triadic Interaction", CVPR, 2019. paper arxiv
-
Datasets
Metrics
Bibtex
@InProceedings{Joo_2019_CVPR,
author = "Joo, Hanbyul and Simon, Tomas and Cikara, Mina and Sheikh, Yaser",
title = "Towards Social Artificial Intelligence: Nonverbal Social Signal Prediction In A Triadic Interaction",
booktitle = "CVPR",
year = "2019"
}
Choudhury et al., "TEMPO: Efficient Multi-View Pose Estimation, Tracking, and Forecasting", ICCV, 2023. paper arxiv code
Wang et al., "Multi-Person 3D Motion Prediction with Multi-Range Transformers", NeurIPS, 2021. paper arxiv code
-
Datasets
Metrics
Bibtex
@InProceedings{Wang_2021_NeurIPS,
author = "Wang, Jiashun and Xu, Huazhe and Narasimhan, Medhini and Wang, Xiaolong",
booktitle = "NeurIPS",
title = "Multi-Person {3D} Motion Prediction with Multi-Range Transformers",
year = "2021"
}
Yasar et al., "A Scalable Approach to Predict Multi-Agent Motion for Human-Robot Collaboration", RAL, 2021. paper
-
Datasets
Metrics
Bibtex
@Article{Yasar_2021_RAL,
author = "Yasar, Mohammad Samin and Iqbal, Tariq",
journal = "RAL",
title = "A Scalable Approach to Predict Multi-Agent Motion for Human-Robot Collaboration",
year = "2021",
volume = "6",
number = "2",
pages = "1686-1693"
}
Bibtex
@InProceedings{Joo_2015_ICCV_2,
author = "Joo, Hanbyul and Liu, Hao and Tan, Lei and Gui, Lin and Nabbe, Bart and Matthews, Iain and Kanade, Takeo and Nobuhara, Shohei and Sheikh, Yaser",
title = "Panoptic Studio: A Massively Multiview System For Social Motion Capture",
booktitle = "ICCV",
year = "2015"
}
SYSU 3DHOI link paper
Used in papers
Foo et al., "ERA: Expert Retrieval and Assembly for Early Action Prediction", ECCV, 2022. paper arxiv
-
Datasets
Metrics
Bibtex
@InProceedings{Foo_2022_ECCV,
author = "Foo, Lin Geng and Li, Tianjiao and Rahmani, Hossein and Ke, Qiuhong and Liu, Jun",
title = "{ERA}: Expert Retrieval and Assembly for Early Action Prediction",
booktitle = "ECCV",
year = "2022"
}
Wang et al., "Progressive Teacher-Student Learning For Early Action Prediction", CVPR, 2019. paper
-
Datasets
Metrics
Bibtex
@InProceedings{Wang_2019_CVPR,
author = "Wang, Xionghui and Hu, Jian-Fang and Lai, Jian-Huang and Zhang, Jianguo and Zheng, Wei-Shi",
title = "Progressive Teacher-Student Learning For Early Action Prediction",
booktitle = "CVPR",
year = "2019"
}
Hu et al., "Real-Time RGB-D Activity Prediction By Soft Regression", ECCV, 2016. paper
-
Datasets
Metrics
Bibtex
@InProceedings{Hu_2016_ECCV,
author = "Hu, Jian-Fang and Zheng, Wei-Shi and Ma, Lianyang and Wang, Gang and Lai, Jianhuang",
editor = "Leibe, Bastian and Matas, Jiri and Sebe, Nicu and Welling, Max",
title = "Real-Time {RGB-D} Activity Prediction By Soft Regression",
booktitle = "ECCV",
year = "2016"
}
Bibtex
@InProceedings{Hu_2015_CVPR,
author = "Hu, Jian-Fang and Zheng, Wei-Shi and Lai, Jianhuang and Zhang, Jianguo",
title = "Jointly Learning Heterogeneous Features For {RGB-D} Activity Recognition",
booktitle = "CVPR",
year = "2015"
}
ActivityNet link paper
Used in papers
Rothfuss et al., "Deep Episodic Memory: Encoding, Recalling, and Predicting Episodic Experiences for Robot Action Execution", RAL, 2018. paper arxiv
-
Datasets
Metrics
Bibtex
@Article{Rothfuss_2018_RAL,
author = "Rothfuss, J. and Ferreira, F. and Aksoy, E. E. and Zhou, Y. and Asfour, T.",
journal = "RAL",
title = "Deep Episodic Memory: Encoding, Recalling, and Predicting Episodic Experiences for Robot Action Execution",
year = "2018",
volume = "3",
number = "4",
pages = "4007-4014"
}
Hosseinzadeh et al., "Video Captioning of Future Frames", WACV, 2021. paper
Bibtex
@InProceedings{Caba_2015_CVPR,
author = "Fabian Caba Heilbron, Victor Escorcia, Bernard Ghanem and Niebles, Juan Carlos",
title = "{ActivityNet}: A Large-Scale Video Benchmark for Human Activity Understanding",
booktitle = "CVPR",
year = "2015"
}
UTD-MHAD link paper
Used in papers
Yasar et al., "VADER: Vector-Quantized Generative Adversarial Network for Motion Prediction", IROS, 2023. paper
Yasar et al., "A Scalable Approach to Predict Multi-Agent Motion for Human-Robot Collaboration", RAL, 2021. paper
-
Datasets
Metrics
Bibtex
@Article{Yasar_2021_RAL,
author = "Yasar, Mohammad Samin and Iqbal, Tariq",
journal = "RAL",
title = "A Scalable Approach to Predict Multi-Agent Motion for Human-Robot Collaboration",
year = "2021",
volume = "6",
number = "2",
pages = "1686-1693"
}
Bibtex
@InProceedings{Chen_2015_ICIP,
author = "Chen, Chen and Jafari, Roozbeh and Kehtarnavaz, Nasser",
booktitle = "ICIP",
title = "{UTD-MHAD}: A Multimodal Dataset for Human Action Recognition Utilizing a Depth Camera and a Wearable Inertial Sensor",
year = "2015"
}
Watch-n-Push (WnP) link paper arxiv
Used in papers
Kataoka et al., "Recognition Of Transitional Action For Short-Term Action Prediction Using Discriminative Temporal CNN Feature", BMVC, 2016. paper
-
Datasets
Metrics
Bibtex
@InProceedings{Kataoka_2016_BMVC,
author = "Kataoka, Hirokatsu and Miyashita, Yudai and Hayashi, Masaki and Iwata, Kenji and Satoh, Yutaka",
title = "Recognition Of Transitional Action For Short-Term Action Prediction Using Discriminative Temporal {CNN} Feature",
year = "2016",
booktitle = "BMVC"
}
Park et al., "HMPO: Human Motion Prediction in Occluded Environments for Safe Motion Planning", RSS, 2020. paper arxiv
-
Datasets
Metrics
Bibtex
@InProceedings{Park_2020_RSS,
AUTHOR = "Park, Jaesung and Manocha, Dinesh",
TITLE = "{HMPO}: Human Motion Prediction in Occluded Environments for Safe Motion Planning",
BOOKTITLE = "RSS",
YEAR = "2020"
}
Bibtex
@InProceedings{Wu_2015_CVPR,
author = "Wu, Chenxia and Zhang, Jiemi and Savarese, Silvio and Saxena, Ashutosh",
title = "{Watch-N-Patch}: Unsupervised Understanding Of Actions And Relations",
booktitle = "CVPR",
year = "2015"
}
WIDER link paper
Used in papers
Safaei et al., "Still Image Action Recognition By Predicting Spatial-Temporal Pixel Evolution", WACV, 2019. paper
-
Datasets
Metrics
Bibtex
@InProceedings{Safaei_2019_WACV,
author = "Safaei, M. and Foroosh, H.",
booktitle = "WACV",
title = "Still Image Action Recognition By Predicting Spatial-Temporal Pixel Evolution",
year = "2019"
}
Bibtex
@InProceedings{Xiong_2015_CVPR,
author = "Xiong, Yuanjun and Zhu, Kai and Lin, Dahua and Tang, Xiaoou",
title = "Recognize Complex Events From Static Images By Fusing Deep Channels",
booktitle = "CVPR",
year = "2015"
}
Georgia Tech Egocentric Activity Gaze+ (GTEA Gaze+) link paper
Used in papers
Shen et al., "Egocentric Activity Prediction Via Event Modulated Attention", ECCV, 2018. paper
-
Datasets
Metrics
Bibtex
@InProceedings{Shen_2018_ECCV,
author = "Shen, Yang and Ni, Bingbing and Li, Zefan and Zhuang, Ning",
title = "Egocentric Activity Prediction Via Event Modulated Attention",
booktitle = "ECCV",
year = "2018"
}
Bibtex
@InProceedings{Li_2015_CVPR,
author = "Li, Yin and Ye, Zhefan and Rehg, James M",
title = "Delving Into Egocentric Actions",
booktitle = "CVPR",
year = "2015"
}
First Person Personalized Activities (FPPA) link paper
Used in papers
Bibtex
@InProceedings{Zhou_2015_ICCV,
author = "Zhou, Yipin and Berg, Tamara L.",
title = "Temporal Perception And Prediction In Ego-Centric Video",
booktitle = "ICCV",
year = "2015"
}
SUN RGB-D link paper
Used in papers
Mottaghi et al., "What Happens If... Learning To Predict The Effect Of Forces In Images", ECCV, 2016. paper arxiv
-
Datasets
Metrics
Bibtex
@InProceedings{Mottaghi_2016_ECCV,
author = "Mottaghi, Roozbeh and Rastegari, Mohammad and Gupta, Abhinav and Farhadi, Ali",
editor = "Leibe, Bastian and Matas, Jiri and Sebe, Nicu and Welling, Max",
title = "What Happens If... Learning To Predict The Effect Of Forces In Images",
booktitle = "ECCV",
year = "2016"
}
Bibtex
@InProceedings{Song_2015_CVPR_2,
author = "Song, Yale and Vallmitjana, J. and Stent, A. and Jaimes, A.",
booktitle = "CVPR",
title = "{TVSum}: Summarizing Web Videos Using Titles",
year = "2015"
}
Amazon link paper arxiv
Used in papers
Bibtex
@InProceedings{Mcauley_2015_CRDIR,
author = "McAuley, Julian and Targett, Christopher and Shi, Qinfeng and Van Den Hengel, Anton",
title = "Image-Based Recommendations On Styles And Substitutes",
booktitle = "SIGIR",
year = "2015"
}
Whole-Body Human Motion (WBHM) link paper
Bibtex
@inproceedings{Mandery_2015_ICAR,
author = "Mandery, Christian and Terlemez, Omer and Do, Martin and Vahrenkamp, Nikolaus and Asfour, Tamim",
title = "The {KIT} whole-body human motion database",
booktitle = "ICAR",
year = "2015"
}
Occlusion MoCap link paper
Used in papers
Park et al., "HMPO: Human Motion Prediction in Occluded Environments for Safe Motion Planning", RSS, 2020. paper arxiv
-
Datasets
Metrics
Bibtex
@InProceedings{Park_2020_RSS,
AUTHOR = "Park, Jaesung and Manocha, Dinesh",
TITLE = "{HMPO}: Human Motion Prediction in Occluded Environments for Safe Motion Planning",
BOOKTITLE = "RSS",
YEAR = "2020"
}
Bibtex
@InProceedings{Dib_IROS_2015,
author = "Dib, Abdallah and Charpillet, François",
title = "Pose Estimation For A Partially Observable Human Body From {RGB-D} Camera",
booktitle = "IROS",
year = "2015"
}
MicroBlog-Images (MBI-1M) link paper
Used in papers
Wang et al., "Retweet Wars: Tweet Popularity Prediction Via Dynamic Multimodal Regression", WACV, 2018. paper
Bibtex
@InProceedings{Cappallo_2015_ICMR,
author = "Cappallo, Spencer and Mensink, Thomas and Snoek, Cees GM",
title = "Latent Factors Of Visual Popularity Prediction",
booktitle = "ICMR",
year = "2015"
}
- Summary: A large-scale dataset of 3D human poses with 3M+ images captured using 11 professional actors in 17 scenarios, such as discussion, smoking, taking photo, etc.
- Applications: Video prediction, Action prediction, Motion prediction
- Data type and annotations: RGB, 3D pose, activity label
- Task: Activity
- Human3.6M
- Custom
- Human3.6M
- Custom
- Human3.6M
- AMASS
- HumanEva-I
- Custom
- Summary: A dataset of 77 hours of a video recording showing 10 breakfast preparation actions performed by 52 subjects in 18 different locations
- Applications: Action prediction
- Data type and annotations: RGB, activity label, temporal segment
- Task: Cooking
- Summary: A large-scale dataset of 1M sports videos with 487 classes
- Applications: Video prediction, Action prediction
- Data type and annotations: RGB, activity label
- Task: Sport
- Summary: A pose detection dataset with 25K images containing 40K subjects performing 410 different activities
- Applications: Motion prediction
- Data type and annotations: RGB, pose, activity label
- Task: Activity
- Summary: A dataset of vehicle data collected in Ann Arbor at 10Hz with associated GPS and vehicle data
- Applications: Trajectory prediction
- Data type and annotations: GPS, Vehicle sensor
- Task: Driving
- Summary: A dataset of RGBD sequences capturing 7 human-object interaction activities including drinking, eating, using a laptop, reading on a cellphone, etc.
- Applications: Action prediction
- Data type and annotations: RGBD, bounding box, 3D pose, activity label
- Task: Activity
- Summary: A dataset of multiple actors engaging in group activities with associated 3D poses recorded in two different environments.
- Applications: Motion prediction
- Data type and annotations: 3D Pose, RGB
- Task: Activity
Human3.6M link paper
Used in papers
Shrivastava et al., "Video Prediction by Modeling Videos as Continuous Multi-Dimensional Processes", CVPR, 2024. paper
Chang et al., "STRPM: A Spatiotemporal Residual Predictive Model for High-Resolution Video Prediction", CVPR, 2022. paper arxiv
-
Datasets
Metrics
Bibtex
@InProceedings{Chang_2022_CVPR,
author = "Chang, Zheng and Zhang, Xinfeng and Wang, Shanshe and Ma, Siwei and Gao, Wen",
title = "{STRPM}: A Spatiotemporal Residual Predictive Model for High-Resolution Video Prediction",
booktitle = "CVPR",
year = "2022"
}
Pourheydari et al., "TaylorSwiftNet: Taylor Driven Temporal Modeling for Swift Future Frame Prediction", BMVC, 2022. paper arxiv
-
Datasets
Metrics
Bibtex
@InProceedings{Pourheydari_2022_BMVC,
author = "Pourheydari, Mohammad Saber and Bahrami, Emad and Fayyaz, Mohsen and Francesca, Gianpiero and Noroozi, Mehdi and Gall, Jürgen",
title = "{TaylorSwiftNet}: Taylor Driven Temporal Modeling for Swift Future Frame Prediction",
booktitle = "BMVC",
year = "2022"
}
Wang et al., "Towards Unified Multi-Excitation for Unsupervised Video Prediction", BMVC, 2022. paper code
-
Datasets
Metrics
Bibtex
@InProceedings{Wang_2022_BMVC,
author = "Wang, Junyan and Likun, Qin and Zhang, Peng and Long, Yang and Hu, Bingzhang and Pagnucco, Maurice and Wang, Shizheng and Song, Yang",
title = "Towards Unified Multi-Excitation for Unsupervised Video Prediction",
booktitle = "BMVC",
year = "2022"
}
Lee et al., "Video Prediction Recalling Long-Term Motion Context via Memory Alignment Learning", CVPR, 2021. paper arxiv code
-
Datasets
Metrics
Bibtex
@InProceedings{Lee_2021_CVPR,
author = "Lee, Sangmin and Kim, Hak Gu and Choi, Dae Hwi and Kim, Hyung-Il and Ro, Yong Man",
title = "Video Prediction Recalling Long-Term Motion Context via Memory Alignment Learning",
booktitle = "CVPR",
year = "2021"
}
Wu et al., "Greedy Hierarchical Variational Autoencoders for Large-Scale Video Prediction", CVPR, 2021. paper arxiv
-
Datasets
Metrics
Bibtex
@InProceedings{Wu_2021_CVPR,
author = "Wu, Bohan and Nair, Suraj and Martin-Martin, Roberto and Fei-Fei, Li and Finn, Chelsea",
title = "Greedy Hierarchical Variational Autoencoders for Large-Scale Video Prediction",
booktitle = "CVPR",
year = "2021"
}
Wu et al., "MotionRNN: A Flexible Model for Video Prediction With Spacetime-Varying Motions", CVPR, 2021. paper arxiv
-
Datasets
Bibtex
@InProceedings{Wu_2021_CVPR_2,
author = "Wu, Haixu and Yao, Zhiyu and Wang, Jianmin and Long, Mingsheng",
title = "{MotionRNN}: A Flexible Model for Video Prediction With Spacetime-Varying Motions",
booktitle = "CVPR",
year = "2021"
}
Gao et al., "Accurate Grid Keypoint Learning for Efficient Video Prediction", IROS, 2021. paper arxiv code
Le et al., "Disentangling Physical Dynamics From Unknown Factors for Unsupervised Video Prediction", CVPR, 2020. paper arxiv code
Franceschi et al., "Stochastic Latent Residual Video Prediction", ICML, 2020. paper arxiv code
-
Datasets
Metrics
Bibtex
@InProceedings{Franceschi_2020_ICML,
author = {Franceschi, Jean-Yves and Delasalles, Edouard and Chen, Micka{\"e}l and Lamprier, Sylvain and Gallinari, Patrick},
title = "Stochastic Latent Residual Video Prediction",
booktitle = "ICML",
year = "2020"
}
Yao et al., "Unsupervised Transfer Learning for Spatiotemporal Predictive Networks", ICML, 2020. paper arxiv code
Xu et al., "Structure Preserving Video Prediction", CVPR, 2018. paper
-
Datasets
Metrics
Bibtex
@InProceedings{Xu_2018_CVPR,
author = "Xu, Jingwei and Ni, Bingbing and Li, Zefan and Cheng, Shuo and Yang, Xiaokang",
title = "Structure Preserving Video Prediction",
booktitle = "CVPR",
year = "2018"
}
Byeon et al., "Contextvp: Fully Context-Aware Video Prediction", ECCV, 2018. paper
Cai et al., "Deep Video Generation, Prediction And Completion Of Human Action Sequences", ECCV, 2018. paper arxiv
Wichers et al., "Hierarchical Long-Term Video Prediction Without Supervision", ICML, 2018. paper arxiv code
Ying et al., "Better Guider Predicts Future Better: Difference Guided Generative Adversarial Networks", ACCV, 2018. paper arxiv
-
Datasets
Metrics
Bibtex
@InProceedings{Ying_2018_ACCV,
author = "Ying, Guohao and Zou, Yingtian and Wan, Lin and Hu, Yiming and Feng, Jiashi",
editor = "Jawahar, C.V. and Li, Hongdong and Mori, Greg and Schindler, Konrad",
title = "Better Guider Predicts Future Better: Difference Guided Generative Adversarial Networks",
booktitle = "ACCV",
year = "2018"
}
Ji et al., "Dynamic Visual Sequence Prediction With Motion Flow Networks", WACV, 2018. paper
Villegas et al., "Learning To Generate Long-Term Future Via Hierarchical Prediction", ICML, 2017. paper arxiv code
-
Datasets
Metrics
Bibtex
@InProceedings{Villegas_2017_ICML,
author = "Villegas, Ruben and Yang, Jimei and Zou, Yuliang and Sohn, Sungryull and Lin, Xunyu and Lee, Honglak",
title = "Learning To Generate Long-Term Future Via Hierarchical Prediction",
booktitle = "ICML",
year = "2017"
}
Finn et al., "Unsupervised Learning For Physical Interaction Through Video Prediction", NeurIPS, 2016. paper arxiv code
Mascaro et al., "Intention-Conditioned Long-Term Human Egocentric Action Anticipation", WACV, 2023. paper
Butepage et al., "Deep Representation Learning For Human Motion Prediction And Classification", CVPR, 2017. paper arxiv
-
Datasets
Metrics
Bibtex
@InProceedings{Butepage_2017_CVPR,
author = "Butepage, Judith and Black, Michael J. and Kragic, Danica and Kjellstrom, Hedvig",
title = "Deep Representation Learning For Human Motion Prediction And Classification",
booktitle = "CVPR",
year = "2017"
}
Eltouny et al., "DE-TGN: Uncertainty-Aware Human Motion Forecasting Using Deep Ensembles", RAL, 2024. paper arxiv
-
Datasets
Bibtex
@ARTICLE{Eltouny_DETGN_2024_RAL,
author = "Eltouny, Kareem A. and Liu, Wansong and Tian, Sibo and Zheng, Minghui and Liang, Xiao",
journal = "RAL",
title = "DE-TGN: Uncertainty-Aware Human Motion Forecasting Using Deep Ensembles",
year = "2024",
volume = "9",
number = "3",
pages = "2192-2199"
}
Mahdavian et al., "STPOTR: Simultaneous Human Trajectory and Pose Prediction Using a Non-Autoregressive Transformer for Robot Follow-Ahead", ICRA, 2023. paper arxiv code
-
Datasets
Metrics
Bibtex
@InProceedings{Mahdavian_2023_ICRA,
author = "Mahdavian, Mohammad and Nikdel, Payam and TaherAhmadi, Mahdi and Chen, Mo",
title = "STPOTR: Simultaneous Human Trajectory and Pose Prediction Using a Non-Autoregressive Transformer for Robot Follow-Ahead",
booktitle = "ICRA",
year = "2023"
}
Nikdel et al., "DMMGAN: Diverse Multi Motion Prediction of 3D Human Joints using Attention-Based Generative Adversarial Network", ICRA, 2023. paper arxiv
Sun et al., "MoML: Online Meta Adaptation for 3D Human Motion Prediction", CVPR, 2024. paper
-
Datasets
Metrics
Bibtex
@InProceedings{Sun_MoML_2024_CVPR,
author = "Sun, Xiaoning and Sun, Huaijiang and Li, Bin and Wei, Dong and Li, Weiqing and Lu, Jianfeng",
title = "MoML: Online Meta Adaptation for 3D Human Motion Prediction",
booktitle = "CVPR",
year = "2024"
}
Chen et al., "Rethinking Human Motion Prediction with Symplectic Integral", CVPR, 2024. paper code
-
Datasets
Metrics
Bibtex
@InProceedings{Chen_Rethinking_2024_CVPR,
author = "Chen, Haipeng and Lyu, Kedi and Liu, Zhenguang and Yin, Yifang and Yang, Xun and Lyu, Yingda",
title = "Rethinking Human Motion Prediction with Symplectic Integral",
booktitle = "CVPR",
year = "2024"
}
Tian et al., "TransFusion: A Practical and Effective Transformer-Based Diffusion Model for 3D Human Motion Prediction", RAL, 2024. paper code
-
Datasets
Bibtex
@ARTICLE{Tian_TransFusion_2024_RAL,
author = "Tian, Sibo and Zheng, Minghui and Liang, Xiao",
journal = "RAL",
title = "TransFusion: A Practical and Effective Transformer-Based Diffusion Model for 3D Human Motion Prediction",
year = "2024",
volume = "9",
number = "7",
pages = "6232-6239"
}
Gao et al., "Decompose More and Aggregate Better: Two Closer Looks at Frequency Representation Learning for Human Motion Prediction", CVPR, 2023. paper
-
Datasets
Metrics
Bibtex
@InProceedings{Gao_2023_CVPR,
author = "Gao, Xuehao and Du, Shaoyi and Wu, Yang and Yang, Yang",
title = "Decompose More and Aggregate Better: Two Closer Looks at Frequency Representation Learning for Human Motion Prediction",
booktitle = "CVPR",
year = "2023"
}
Sun et al., "DeFeeNet: Consecutive 3D Human Motion Prediction With Deviation Feedback", CVPR, 2023. paper arxiv
Xu et al., "Uncovering the Missing Pattern: Unified Framework Towards Trajectory Imputation and Prediction", CVPR, 2023. paper arxiv code
Barquero et al., "BeLFusion: Latent Diffusion for Behavior-Driven Human Motion Prediction", ICCV, 2023. paper arxiv code
Choudhury et al., "TEMPO: Efficient Multi-View Pose Estimation, Tracking, and Forecasting", ICCV, 2023. paper arxiv code
Cui et al., "Test-time Personalizable Forecasting of 3D Human Poses", ICCV, 2023. paper
-
Datasets
Metrics
Bibtex
@InProceedings{Cui_2023_ICCV,
author = "Cui, Qiongjie and Sun, Huaijiang and Lu, Jianfeng and Li, Weiqing and Li, Bin and Yi, Hongwei and Wang, Haofan",
title = "Test-time Personalizable Forecasting of 3D Human Poses",
booktitle = "ICCV",
year = "2023"
}
Xing et al., "HDG-ODE: A Hierarchical Continuous-Time Model for Human Pose Forecasting", ICCV, 2023. paper arxiv
Chen et al., "HumanMAC: Masked Motion Completion for Human Motion Prediction", ICCV, 2023. paper arxiv code
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Datasets
Metrics
Bibtex
@InProceedings{Chen_2023_ICCV_1,
author = "Chen, Ling-Hao and Zhang, JiaWei and Li, Yewen and Pang, Yiren and Xia, Xiaobo and Liu, Tongliang",
title = "HumanMAC: Masked Motion Completion for Human Motion Prediction",
booktitle = "ICCV",
year = "2023"
}
Xu et al., "Auxiliary Tasks Benefit 3D Skeleton-based Human Motion Prediction", ICCV, 2023. paper arxiv code
-
Datasets
Metrics
Bibtex
@InProceedings{Xu_2023_ICCV_1,
author = "Xu, Chenxin and Tan, Robby T. and Tan, Yuhong and Chen, Siheng and Wang, Xinchao and Wang, Yanfeng",
title = "Auxiliary Tasks Benefit 3D Skeleton-based Human Motion Prediction",
booktitle = "ICCV",
year = "2023"
}
Ahn et al., "Can We Use Diffusion Probabilistic Models for 3D Motion Prediction?", ICRA, 2023. paper arxiv
Saadatnejad et al., "A generic diffusion-based approach for 3D human pose prediction in the wild", ICRA, 2023. paper arxiv
-
Datasets
Metrics
Bibtex
@InProceedings{Saadatnejad_2023_ICRA,
author = "Saadatnejad, Saeed and Rasekh, Ali and Mofayezi, Mohammadreza and Medghalchi, Yasamin and Rajabzadeh, Sara and Mordan, Taylor and Alahi, Alexandre",
title = "A generic diffusion-based approach for 3D human pose prediction in the wild",
booktitle = "ICRA",
year = "2023"
}
Guo et al., "Back to MLP: A Simple Baseline for Human Motion Prediction", WACV, 2023. paper arxiv code
-
Datasets
Metrics
Bibtex
@InProceedings{Guo_2023_WACV,
author = "Guo, Wen and Du, Yuming and Shen, Xi and Lepetit, Vincent and Alameda-Pineda, Xavier and Moreno-Noguer, Francesc",
title = "Back to MLP: A Simple Baseline for Human Motion Prediction",
booktitle = "WACV",
year = "2023"
}
Ma et al., "Multi-Objective Diverse Human Motion Prediction With Knowledge Distillation", CVPR, 2022. paper
-
Datasets
Metrics
Bibtex
@InProceedings{Ma_2022_CVPR_2,
author = "Ma, Hengbo and Li, Jiachen and Hosseini, Ramtin and Tomizuka, Masayoshi and Choi, Chiho",
title = "Multi-Objective Diverse Human Motion Prediction With Knowledge Distillation",
booktitle = "CVPR",
year = "2022"
}
Ma et al., "Progressively Generating Better Initial Guesses Towards Next Stages for High-Quality Human Motion Prediction", CVPR, 2022. paper arxiv code
-
Datasets
Metrics
Bibtex
@InProceedings{Ma_2022_CVPR,
author = "Ma, Tiezheng and Nie, Yongwei and Long, Chengjiang and Zhang, Qing and Li, Guiqing",
title = "Progressively Generating Better Initial Guesses Towards Next Stages for High-Quality Human Motion Prediction",
booktitle = "CVPR",
year = "2022"
}
Salzmann et al., "Motron: Multimodal Probabilistic Human Motion Forecasting", CVPR, 2022. paper arxiv code
Zhong et al., "Spatio-Temporal Gating-Adjacency GCN for Human Motion Prediction", CVPR, 2022. paper arxiv
Li et al., "Skeleton-Parted Graph Scattering Networks for 3D Human Motion Prediction", ECCV, 2022. paper arxiv code
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Datasets
Metrics
Bibtex
@InProceedings{Li_2022_ECCV,
author = "Li, Maosen and Chen, Siheng and Zhang, Zijing and Xie, Lingxi and Tian, Qi and Zhang, Ya",
title = "Skeleton-Parted Graph Scattering Networks for {3D} Human Motion Prediction",
booktitle = "ECCV",
year = "2022"
}
Sampieri et al., "Pose Forecasting in Industrial Human-Robot Collaboration", ECCV, 2022. paper arxiv code
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Datasets
Metrics
Bibtex
@InProceedings{Sampieri_2022_ECCV,
author = "Sampieri, Alessio and di Melendugno, Guido Maria D’Amely and Avogaro, Andrea and Cunico, Federico and Setti, Francesco and Skenderi, Geri and Cristani, Marco and Galasso, Fabio",
title = "Pose Forecasting in Industrial Human-Robot Collaboration",
booktitle = "ECCV",
year = "2022"
}
Sun et al., "Overlooked Poses Actually Make Sense: Distilling Privileged Knowledge for Human Motion Prediction", ECCV, 2022. paper arxiv
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Datasets
Metrics
Bibtex
@InProceedings{Sun_2022_ECCV,
author = "Sun, Xiaoning and Cui, Qiongjie and Sun, Huaijiang and Li, Bin and Li, Weiqing and Lu, Jianfeng",
title = "Overlooked Poses Actually Make Sense: Distilling Privileged Knowledge for Human Motion Prediction",
booktitle = "ECCV",
year = "2022"
}
Xu et al., "Diverse Human Motion Prediction Guided by Multi-level Spatial-Temporal Anchors", ECCV, 2022. paper code
Mascaro et al., "Robust Human Motion Forecasting using Transformer-based Model", IROS, 2022. paper arxiv
Zhang et al., "IMNet: Physics-Infused Neural Network for Human Motion Prediction", RAL, 2022. paper
Sun et al., "Action-guided 3D Human Motion Prediction", NeurIPS, 2021. paper
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Datasets
Metrics
Bibtex
@InProceedings{Sun_2021_NeurIPS,
author = "Sun, Jiangxin and Lin, Zihang and Han, Xintong and Hu, Jian-Fang and Xu, Jia and Zheng, Wei-Shi",
booktitle = "NeurIPS",
title = "Action-guided {3D} Human Motion Prediction",
year = "2021"
}
Cui et al., "Towards Accurate 3D Human Motion Prediction From Incomplete Observations", CVPR, 2021. paper
Li et al., "RAIN: Reinforced Hybrid Attention Inference Network for Motion Forecasting", ICCV, 2021. paper arxiv
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Datasets
Metrics
Bibtex
@InProceedings{Li_2021_ICCV_2,
author = "Li, Jiachen and Yang, Fan and Ma, Hengbo and Malla, Srikanth and Tomizuka, Masayoshi and Choi, Chiho",
title = "{RAIN}: Reinforced Hybrid Attention Inference Network for Motion Forecasting",
booktitle = "ICCV",
year = "2021"
}
Aliakbarian et al., "Contextually Plausible and Diverse 3D Human Motion Prediction", ICCV, 2021. paper arxiv
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Datasets
Metrics
Bibtex
@InProceedings{Aliakbarian_2021_ICCV,
author = "Aliakbarian, Sadegh and Saleh, Fatemeh and Petersson, Lars and Gould, Stephen and Salzmann, Mathieu",
title = "Contextually Plausible and Diverse {3D} Human Motion Prediction",
booktitle = "ICCV",
year = "2021"
}
Dang et al., "MSR-GCN: Multi-Scale Residual Graph Convolution Networks for Human Motion Prediction", ICCV, 2021. paper code
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Datasets
Metrics
Bibtex
@InProceedings{Dang_2021_ICCV,
author = "Dang, Lingwei and Nie, Yongwei and Long, Chengjiang and Zhang, Qing and Li, Guiqing",
title = "{MSR-GCN}: Multi-Scale Residual Graph Convolution Networks for Human Motion Prediction",
booktitle = "ICCV",
year = "2021"
}
Liu et al., "Motion Prediction Using Trajectory Cues", ICCV, 2021. paper code
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Datasets
Metrics
Bibtex
@InProceedings{Liu_2021_ICCV,
author = "Liu, Zhenguang and Su, Pengxiang and Wu, Shuang and Shen, Xuanjing and Chen, Haipeng and Hao, Yanbin and Wang, Meng",
title = "Motion Prediction Using Trajectory Cues",
booktitle = "ICCV",
year = "2021"
}
Mao et al., "Generating Smooth Pose Sequences for Diverse Human Motion Prediction", ICCV, 2021. paper arxiv
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Datasets
Metrics
Bibtex
@InProceedings{Mao_2021_ICCV,
author = "Mao, Wei and Liu, Miaomiao and Salzmann, Mathieu",
title = "Generating Smooth Pose Sequences for Diverse Human Motion Prediction",
booktitle = "ICCV",
year = "2021"
}
Sofianos et al., "Space-Time-Separable Graph Convolutional Network for Pose Forecasting", ICCV, 2021. paper code
Li et al., "Directed Acyclic Graph Neural Network for Human Motion Prediction", ICRA, 2021. paper code
Xu et al., "Probabilistic Human Motion Prediction via A Bayesian Neural Network", ICRA, 2021. paper arxiv
Zhang et al., "Non-local Graph Convolutional Network for Joint Activity Recognition and Motion Prediction", IROS, 2021. paper arxiv
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Datasets
Metrics
Bibtex
@InProceedings{Zhang_2021_IROS,
author = "Zhang, Dianhao and Vien, Ngo Anh and Van, Mien and McLoone, Seán",
booktitle = "IROS",
title = "Non-local Graph Convolutional Network for Joint Activity Recognition and Motion Prediction",
year = "2021"
}
Aliakbarian et al., "A Stochastic Conditioning Scheme for Diverse Human Motion Prediction", CVPR, 2020. paper code
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Datasets
Metrics
Bibtex
@InProceedings{Aliakbarian_2020_CVPR,
author = "Aliakbarian, Sadegh and Saleh, Fatemeh Sadat and Salzmann, Mathieu and Petersson, Lars and Gould, Stephen",
title = "A Stochastic Conditioning Scheme for Diverse Human Motion Prediction",
booktitle = "CVPR",
year = "2020"
}
Li et al., "Dynamic Multiscale Graph Neural Networks for 3D Skeleton Based Human Motion Prediction", CVPR, 2020. paper arxiv code
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Datasets
Metrics
Bibtex
@InProceedings{Li_2020_CVPR,
author = "Li, Maosen and Chen, Siheng and Zhao, Yangheng and Zhang, Ya and Wang, Yanfeng and Tian, Qi",
title = "Dynamic Multiscale Graph Neural Networks for {3D} Skeleton Based Human Motion Prediction",
booktitle = "CVPR",
year = "2020"
}
Cai et al., "Learning Progressive Joint Propagation for Human Motion Prediction", ECCV, 2020. paper
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Datasets
Metrics
Bibtex
@InProceedings{Cai_2020_ECCV,
author = "Cai, Yujun and Huang, Lin and Wang, Yiwei and Cham, Tat-Jen and Cai, Jianfei and Yuan, Junsong and Liu, Jun and Yang, Xu and Zhu, Yiheng and Shen, Xiaohui and Liu, Ding and Liu, Jing and Thalmann, Nadia M",
title = "Learning Progressive Joint Propagation for Human Motion Prediction",
booktitle = "ECCV",
year = "2020"
}
Mao et al., "History Repeats Itself: Human Motion Prediction via Motion Attention", ECCV, 2020. paper arxiv code
Piergiovanni et al., "Adversarial Generative Grammars for Human Activity Prediction", ECCV, 2020. paper arxiv
Yuan et al., "DLow: Diversifying Latent Flows for Diverse Human Motion Prediction", ECCV, 2020. paper arxiv code
Chao et al., "Adversarial Refinement Network for Human Motion Prediction", ACCV, 2020. paper arxiv code
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Datasets
Metrics
Bibtex
@InProceedings{Chao_2020_ACCV,
author = "Chao, Xianjin and Bin, Yanrui and Chu, Wenqing and Cao, Xuan and Ge, Yanhao and Wang, Chengjie and Li, Jilin and Huang, Feiyue and Leung, Howard",
title = "Adversarial Refinement Network for Human Motion Prediction",
booktitle = "ACCV",
year = "2020"
}
Gopalakrishnan et al., "A Neural Temporal Model For Human Motion Prediction", CVPR, 2019. paper arxiv code
Liu et al., "Towards Natural And Accurate Future Motion Prediction Of Humans And Animals", CVPR, 2019. paper code
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Datasets
Metrics
Bibtex
@InProceedings{Liu_2019_CVPR,
author = "Liu, Zhenguang and Wu, Shuang and Jin, Shuyuan and Liu, Qi and Lu, Shijian and Zimmermann, Roger and Cheng, Li",
title = "Towards Natural And Accurate Future Motion Prediction Of Humans And Animals",
booktitle = "CVPR",
year = "2019"
}
Hernandez et al., "Human Motion Prediction Via Spatio-Temporal Inpainting", ICCV, 2019. paper arxiv code
Mao et al., "Learning Trajectory Dependencies For Human Motion Prediction", ICCV, 2019. paper arxiv code
Zhang et al., "Predicting 3D Human Dynamics From Video", ICCV, 2019. paper arxiv code
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Datasets
Metrics
Bibtex
@InProceedings{Zhang_2019_ICCV,
author = "Zhang, Jason Y. and Felsen, Panna and Kanazawa, Angjoo and Malik, Jitendra",
title = "Predicting {3D} Human Dynamics From Video",
booktitle = "ICCV",
year = "2019"
}
Chiu et al., "Action-Agnostic Human Pose Forecasting", WACV, 2019. paper arxiv code
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Datasets
Metrics
Bibtex
@InProceedings{Chiu_2019_WACV,
author = "Chiu, H. and Adeli, E. and Wang, B. and Huang, D. and Niebles, J. C.",
booktitle = "WACV",
title = "Action-Agnostic Human Pose Forecasting",
year = "2019"
}
Gui et al., "Few-Shot Human Motion Prediction Via Meta-Learning", ECCV, 2018. paper
Gui et al., "Adversarial Geometry-Aware Human Motion Prediction", ECCV, 2018. paper
Gui et al., "Teaching Robots To Predict Human Motion", IROS, 2018. paper
Chao et al., "Forecasting Human Dynamics From Static Images", CVPR, 2017. paper arxiv code
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Datasets
Metrics
Bibtex
@InProceedings{Chao_2017_CVPR,
author = "Chao, Yu-Wei and Yang, Jimei and Price, Brian and Cohen, Scott and Deng, Jia",
title = "Forecasting Human Dynamics From Static Images",
booktitle = "CVPR",
year = "2017"
}
Martinez et al., "On Human Motion Prediction Using Recurrent Neural Networks", CVPR, 2017. paper arxiv code
Bibtex
@Article{Ionescu_2014_PAMI,
author = "Ionescu, Catalin and Papava, Dragos and Olaru, Vlad and Sminchisescu, Cristian",
title = "{Human3.6M}: Large Scale Datasets And Predictive Methods For {3D} Human Sensing In Natural Environments",
journal = "PAMI",
volume = "36",
number = "7",
pages = "1325-1339",
year = "2014"
}
Breakfast link paper
Used in papers
Girase et al., "Latency Matters: Real-Time Action Forecasting Transformer", CVPR, 2023. paper code
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Datasets
Metrics
Bibtex
@InProceedings{Girase_2023_CVPR,
author = "Girase, Harshayu and Agarwal, Nakul and Choi, Chiho and Mangalam, Karttikeya",
title = "Latency Matters: Real-Time Action Forecasting Transformer",
booktitle = "CVPR",
year = "2023"
}
Nawhal et al., "Rethinking Learning Approaches for Long-Term Action Anticipation", ECCV, 2022. paper arxiv code
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Datasets
Metrics
Bibtex
@InProceedings{Nawhal_2022_ECCV,
author = "Nawhal, Megha and Jyothi, Akash Abdu and Mori, Greg",
title = "Rethinking Learning Approaches for Long-Term Action Anticipation",
booktitle = "ECCV",
year = "2022"
}
Roy et al., "Action Anticipation Using Latent Goal Learning", WACV, 2022. paper code
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Datasets
Metrics
Bibtex
@InProceedings{Roy_2022_WACV,
author = "Roy, Debaditya and Fernando, Basura",
title = "Action Anticipation Using Latent Goal Learning",
booktitle = "WACV",
year = "2022"
}
Zhao et al., "On Diverse Asynchronous Activity Anticipation", ECCV, 2020. paper
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Datasets
Metrics
Bibtex
@InProceedings{Zhao_2020_ECCV,
author = "Zhao, He and Wildes, Richard P.",
title = "On Diverse Asynchronous Activity Anticipation",
booktitle = "ECCV",
year = "2020"
}
Gammulle et al., "Forecasting Future Action Sequences With Neural Memory Networks", BMVC, 2019. paper arxiv
Alati et al., "Help By Predicting What To Do", ICIP, 2019. paper
Bibtex
@InProceedings{Kuehne_2014_CVPR,
author = "Kuehne, H. and Arslan, A. B. and Serre, T.",
title = "The Language Of Actions: Recovering The Syntax And Semantics Of Goal-Directed Human Activities",
booktitle = "CVPR",
year = "2014"
}
Sports-1M link paper
Used in papers
Lu et al., "Flexible Spatio-Temporal Networks For Video Prediction", CVPR, 2017. paper
Bhattacharjee et al., "Temporal Coherency Based Criteria For Predicting Video Frames Using Deep Multi-Stage Generative Adversarial Networks", NeurIPS, 2017. paper
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Datasets
Metrics
Bibtex
@InProceedings{Bhattacharjee_2017_NeurIPS,
author = "Bhattacharjee, Prateep and Das, Sukhendu",
title = "Temporal Coherency Based Criteria For Predicting Video Frames Using Deep Multi-Stage Generative Adversarial Networks",
booktitle = "NeurIPS",
year = "2017"
}
Kong et al., "Deep Sequential Context Networks For Action Prediction", CVPR, 2017. paper
Bibtex
@InProceedings{Karpathy_2014_CVPR,
author = "Karpathy, Andrej and Toderici, George and Shetty, Sanketh and Leung, Thomas and Sukthankar, Rahul and Fei-Fei, Li",
title = "Large-Scale Video Classification With Convolutional Neural Networks",
year = "2014",
booktitle = "CVPR"
}
MPII Human Pose link paper
Used in papers
Chao et al., "Forecasting Human Dynamics From Static Images", CVPR, 2017. paper arxiv code
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Datasets
Metrics
Bibtex
@InProceedings{Chao_2017_CVPR,
author = "Chao, Yu-Wei and Yang, Jimei and Price, Brian and Cohen, Scott and Deng, Jia",
title = "Forecasting Human Dynamics From Static Images",
booktitle = "CVPR",
year = "2017"
}
Bibtex
@InProceedings{Andriluka_2014_CVPR,
author = "Andriluka, Mykhaylo and Pishchulin, Leonid and Gehler, Peter and Schiele, Bernt",
title = "{2D} Human Pose Estimation: New Benchmark And State Of The Art Analysis",
booktitle = "CVPR",
year = "2014"
}
Safety Pilot Model Deployment (SPMD) link paper
Used in papers
Bibtex
@Techreport{Bezzina_2014_tech,
author = "Bezzina, Debby and Sayer, James",
title = "Safety Pilot Model Deployment: Test Conductor Team Report",
institution = "NHTSA",
year = "2014"
}
Online RGBD Action Dataset (ORGBD) link paper
Used in papers
Hu et al., "Real-Time RGB-D Activity Prediction By Soft Regression", ECCV, 2016. paper
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Datasets
Metrics
Bibtex
@InProceedings{Hu_2016_ECCV,
author = "Hu, Jian-Fang and Zheng, Wei-Shi and Ma, Lianyang and Wang, Gang and Lai, Jianhuang",
editor = "Leibe, Bastian and Matas, Jiri and Sebe, Nicu and Welling, Max",
title = "Real-Time {RGB-D} Activity Prediction By Soft Regression",
booktitle = "ECCV",
year = "2016"
}
Bibtex
@InProceedings{Yu_2015_ACCV,
author = "Yu, Gang and Liu, Zicheng and Yuan, Junsong",
editor = "Cremers, Daniel and Reid, Ian and Saito, Hideo and Yang, Ming-Hsuan",
title = "Discriminative Orderlet Mining For Real-Time Recognition Of Human-Object Interaction",
booktitle = "ACCV",
year = "2015"
}
Campus and Shelf (CaS) link paper
Used in papers
Bibtex
@inproceedings{Belagian_2014_CVPR,
author = "Belagiannis, Vasileios and Amin, Sikandar and Andriluka, Mykhaylo and Schiele, Bernt and Navab, Nassir and Ilic, Slobodan",
title = "{3D} Pictorial Structures for Multiple Human Pose Estimation",
booktitle = "CVPR",
year = "2014"
}