🔥A curated list of awesome Diffusion Models(DMs) in low-level vision.🔥
Please feel free to offer your suggestions in the Issues and pull requests to add links.
[ Last updated at 2024/07/18 ]
Reti-Diff: Illumination Degradation Image Restoration with Retinex-based Latent Diffusion Model
Chunming He, Chengyu Fang, Yulun Zhang, Kai Li, Longxiang Tang, Chenyu You, Fengyang Xiao, Zhenhua Guo, Xiu Li
arXiv 2023. [Paper] [Code]
Nov. 2023
Release | Method | Title | Pub. | Link |
---|---|---|---|---|
2023/05 | DiffPIR | Denoising diffusion models for plug-and-play image restoration Yuanzhi Zhu, Kai Zhang, Jingyun Liang, Jiezhang Cao, Bihan Wen, Radu Timofte, Luc Van Gool |
CVPR 2023 |
Paper/Code |
2023/05 | RED-Diff | A Variational Perspective on Solving Inverse Problems with Diffusion Models Morteza Mardani, Jiaming Song, Jan Kautz, Arash Vahdat |
arXiv 2023 |
Paper/ |
2023/04 | GDP | Generative Diffusion Prior for Unified Image Restoration and Enhancement Ben Fei, Zhaoyang Lyu, Liang Pan, Junzhe Zhang, Weidong Yang, Tianyue Luo, Bo Zhang, Bo Dai |
CVPR 2023 |
Paper/Code |
2023/04 | - | Score-Based Diffusion Models as Principled Priors for Inverse Imaging Berthy T. Feng, Jamie Smith, Michael Rubinstein, Huiwen Chang, Katherine L. Bouman, William T. Freeman |
arXiv 2023 |
Paper/ |
2023/02 | πGDM | Pseudoinverse-Guided Diffusion Models for Inverse Problems Jiaming Song, Arash Vahdat, Morteza Mardani, Jan Kautz |
ICLR 2023 |
Paper/ |
2022/12 | ADIR | ADIR: Adaptive Diffusion for Image Reconstruction Shady Abu-Hussein, Tom Tirer, Raja Giryes |
arXiv 2022 |
Paper/ |
2022/12 | DDNM | Zero-Shot Image Restoration Using Denoising Diffusion Null-Space Model Yinhuai Wang, Jiwen Yu, Jian Zhang |
ICLR 2023 |
Paper/Code |
2022/09 | DPS | Diffusion Posterior Sampling for General Noisy Inverse Problems Hyungjin Chung, Jeongsol Kim, Michael T. Mccann, Marc L. Klasky, Jong Chul Ye |
CVPR 2023 |
Paper/Code |
2022/01 | MCG | Improving diffusion models for inverse problems using manifold constraints Hyungjin Chung, Byeongsu Sim, Dohoon Ryu, Jong Chul Ye |
NIPS 2022 |
Paper/Code |
2022/01 | DDRM | Denoising Diffusion Restoration Models Bahjat Kawar, Michael Elad, Stefano Ermon, Jiaming Song |
NIPS 2022 |
Paper/Code |
2021/12 | CCDF | Come-Closer-Diffuse-Faster: Accelerating Conditional Diffusion Models for Inverse Problems through Stochastic Contraction Hyungjin Chung, Byeongsu Sim, Jong Chul Ye |
CVPR 2022 |
Paper/ |
2021/08 | ILVR | ILVR: Conditioning Method for Denoising Diffusion Probabilistic Models Jooyoung Choi, Sungwon Kim, Yonghyun Jeong, Youngjune Gwon, Sungroh Yoon |
ICCV 2021 |
Paper/Code |
2021/05 | SNIPS | SNIPS: Solving Noisy Inverse Problems Stochastically Bahjat Kawar, Gregory Vaksman, Michael Elad |
NIPS 2021 |
Paper/Code |
Release | Method | Title | Pub. | Link |
---|---|---|---|---|
2024/03 | DiffUIR | Selective Hourglass Mapping for Universal Image Restoration Based on Diffusion Model Dian Zheng, Xiao-Ming Wu, Shuzhou Yang, Jian Zhang, Jian-Fang Hu, Wei-Shi Zheng |
CVPR 2024 |
Paper/Code |
2024/03 | - | Efficient Diffusion Model for Image Restoration by Residual Shifting Yuanzhi Zhu, Kai Zhang, Jingyun Liang, Jiezhang Cao, Bihan Wen, Radu Timofte, Luc Van Gool |
arXiv 2024 |
Paper/Code |
2023/08 | RDDM | Residual Denoising Diffusion Models Jiawei Liu, Qiang Wang, Huijie Fan, Yinong Wang, Yandong Tang, Liangqiong Qu |
CVPR 2024 |
Paper/Code |
2023/08 | DiffBIR | DiffBIR: Towards Blind Image Restoration with Generative Diffusion Prior Xinqi Lin, Jingwen He, Ziyan Chen, Zhaoyang Lyu, Bo Dai, Fanghua Yu, Wanli Ouyang, Yu Qiao, Chao Dong |
arXiv 2023 |
Paper/Code |
2023/05 | InDI | Inversion by Direct Iteration: An Alternative to Denoising Diffusion for Image Restoration Mauricio Delbracio, Peyman Milanfar |
arXiv 2023 |
Paper/Code |
2023/03 | DiracDiffusion | DiracDiffusion: Denoising and Incremental Reconstruction with Assured Data-Consistency Zalan Fabian, Berk Tinaz, Mahdi Soltanolkotabi |
arXiv 2023 |
Paper/ |
2023/04 | Refusion | Refusion: Enabling Large-Size Realistic Image Restoration with Latent-Space Diffusion Models Ziwei Luo, Fredrik K. Gustafsson, Zheng Zhao, Jens Sjölund, Thomas B. Schön |
CVPRW 2023 |
Paper/Code |
2023/01 | IR-SDE | Image Restoration with Mean-Reverting Stochastic Differential Equations Ziwei Luo, Fredrik K. Gustafsson, Zheng Zhao, Jens Sjölund, Thomas B. Schön |
ICML 2023 |
Paper/Code |
2021/12 | LDM | High-resolution image synthesis with latent diffusion models Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, Björn Ommer |
CVPR 2022 |
Paper/Code |
Release | Method | Title | Pub. | Link |
---|---|---|---|---|
2023/11 | CoSeR | CoSeR: Bridging Image and Language for Cognitive Super-Resolution Haoze Sun, Wenbo Li, Jianzhuang Liu, Haoyu Chen, Renjing Pei, Xueyi Zou, Youliang Yan, Yujiu Yang |
arXiv 2023 |
Paper/Code |
2023/09 | - | License Plate Super-Resolution Using Diffusion Models Sawsan AlHalawani, Bilel Benjdira, Adel Ammar, Anis Koubaa, Anas M. Ali |
arXiv 2023 |
Paper/ |
2023/08 | PASD | Pixel-Aware Stable Diffusion for Realistic Image Super-resolution and Personalized Stylization Tao Yang, Rongyuan Wu, Peiran Ren, Xuansong Xie, Lei Zhang |
arXiv 2023 |
Paper/Code |
2023/07 | ResShift | ResShift: Efficient Diffusion Model for Image Super-resolution by Residual Shifting Zongsheng Yue, Jianyi Wang, Chen Change Loy |
NIPS 2023 |
Paper/Code |
2023/07 | PartDiff | PartDiff: Image Super-resolution with Partial Diffusion Models Axi Niu, Pham Xuan Trung, Kang Zhang, Jinqiu Sun, Yu Zhu, In So Kweon, Yanning Zhang |
arXiv 2023 |
Paper/ |
2023/07 | ACDMSR | ACDMSR: Accelerated Conditional Diffusion Models for Single Image Super-Resolution Axi Niu, Pham Xuan Trung, Kang Zhang, Jinqiu Sun, Yu Zhu, In So Kweon, Yanning Zhang |
IEEE Trans. Broadcast. 2024 |
Paper/ |
2023/05 | StableSR | Exploiting Diffusion Prior for Real-World Image Super-Resolution Jianyi Wang, Zongsheng Yue, Shangchen Zhou, Kelvin C.K. Chan, Chen Change Loy |
arXiv 2023 |
Paper/Code |
2023/03 | DR2 | DR2: Diffusion-Based Robust Degradation Remover for Blind Face Restoration Zhixin Wang, Xiaoyun Zhang, Ziying Zhang, Huangjie Zheng, Mingyuan Zhou, Ya Zhang, Yanfeng Wang |
CVPR 2023 |
Paper/Code |
2023/03 | ResDiff | ResDiff: Combining CNN and Diffusion Model for Image Super-Resolution Shuyao Shang, Zhengyang Shan, Guangxing Liu, Jinglin Zhang |
AAAI 2024 |
Paper/Code |
2023/03 | IDM | Implicit Diffusion Models for Continuous Super-Resolution Sicheng Gao, Xuhui Liu, Bohan Zeng, Sheng Xu, Yanjing Li, Xiaoyan Luo, Jianzhuang Liu, Xiantong Zhen, Baochang Zhang |
CVPR 2023 |
Paper/Code |
2023/02 | - | Denoising Diffusion Probabilistic Models for Robust Image Super-Resolution in the Wild Hshmat Sahak, Daniel Watson, Chitwan Saharia, David Fleet |
arXiv 2023 |
Paper/ |
2023/02 | CDPMSR | CDPMSR: Conditional Diffusion Probabilistic Models for Single Image Super-Resolution Axi Niu, Kang Zhang, Trung X. Pham, Jinqiu Sun, Yu Zhu, In So Kweon, Yanning Zhang |
arXiv 2023 |
Paper/ |
2022/09 | SUE-SR | Face Super-Resolution Using Stochastic Differential Equations Marcelo dos Santos, Rayson Laroca, Rafael O. Ribeiro, João Neves, Hugo Proença, David Menotti |
SIGGRAPH 2022 |
Paper/Code |
2021/05 | CDM | Cascaded Diffusion Models for High Fidelity Image Generation Jonathan Ho, Chitwan Saharia, William Chan, David J. Fleet, Mohammad Norouzi, Tim Salimans. |
JMLR 2022 |
Paper/Code |
2021/04 | SR3 | Image Super-Resolution via Iterative Refinement Chitwan Saharia, Jonathan Ho, William Chan, Tim Salimans, David J. Fleet, Mohammad Norouzi. |
TPAMI 2022 |
Paper/Code |
2021/04 | SRDiff | SRDiff: Single Image Super-Resolution with Diffusion Probabilistic Models H. Li, Y. Yang, M. Chang, S. Chen, H. Feng, Z. Xu, Q. Li, and Y. Chen. |
Neurocomputing 2022 |
Paper/Code |
Release | Method | Title | Pub. | Link |
---|---|---|---|---|
2024/03 | MMGInpainting | MMGInpainting: Multi-Modality Guided Image Inpainting Based On Diffusion Models Cong Zhang, Wenxia Yang, Xin Li, Huan Han |
IEEE Trans Multimedia 2024 |
Paper/Code |
2024/03 | BrushNet | BrushNet: A Plug-and-Play Image Inpainting Model with Decomposed Dual-Branch Diffusion Xuan Ju, Xian Liu, Xintao Wang, Yuxuan Bian, Ying Shan, Qiang Xu |
arXiv 2024 |
Paper/Code |
2024/03 | - | Fill in the ____ (a Diffusion-based Image Inpainting Pipeline) Eyoel Gebre, Krishna Saxena, Timothy Tran |
arXiv 2024 |
Paper/ |
2023/09 | Gradpaint | Gradpaint: Gradient-Guided Inpainting with Diffusion Models Asya Grechka, Guillaume Couairon, Matthieu Cord |
CVIU 2024 |
Paper/ |
2022/05 | Palette | Palette: Image-to-image diffusion models C. Saharia, W. Chan, H. Chang, C. Lee, J. Ho, T. Salimans, D. Fleet, and M. Norouzi. |
SIGGRAPH 2022 |
Paper/Code |
2022/01 | RePaint | Repaint: Inpainting using denoising diffusion probabilistic models A. Lugmayr, M. Danelljan, A. Romero, F. Yu, R. Timofte, and L. Van Gool. |
CVPR 2022 |
Paper/Code |
Release | Method | Title | Pub. | Link |
---|---|---|---|---|
2024/04 | Diffevent | Diffevent: Event Residual Diffusion for Image Deblurring Pei Wang, Jiumei He, Qingsen Yan, Yu Zhu, Jinqiu Sun, Yanning Zhang |
ICASSP 2024 |
Paper/Code |
2024/01 | FastDiffusionEM | Fast Diffusion EM: a diffusion model for blind inverse problems with application to deconvolution Charles Laroche, Andrés Almansa, Eva Coupete |
WACV 2024 |
Paper/Code |
2024/01 | SI-DDPM-FMO | Single-Image Deblurring, Trajectory and Shape Recovery of Fast Moving Objects With Denoising Diffusion Probabilistic Models Radim Spetlik, Denys Rozumnyi, Jiří Matas |
WACV 2024 |
Paper/Code |
2023/05 | HI-Diff | Hierarchical Integration Diffusion Model for Realistic Image Deblurring Zheng Chen, Yulun Zhang, Ding Liu, Bin Xia, Jinjin Gu, Linghe Kong, Xin Yuan |
arXiv 2023 |
Paper/ |
2022/12 | - | Multiscale Structure Guided Diffusion for Image Deblurring M. Ren, M. Delbracio, H. Talebi, G. Gerig, and P. Milanfar. |
ICCV 2023 |
Paper/ |
2021/12 | DVSR | Deblurring via Stochastic Refinement Jay Whang, Mauricio Delbracio, Hossein Talebi, Chitwan Saharia, Alexandros G. Dimakis, Peyman Milanfar |
CVPR 2022 |
Paper/Code |
Release | Method | Title | Pub. | Link |
---|---|---|---|---|
2023/08 | HazeAug | Frequency Compensated Diffusion Model for Real-scene Dehazing Jing Wang, Songtao Wu, Kuanhong Xu, Zhiqiang Yuan |
Neural Networks 2024 |
Paper/Code |
2022/11 | WeatherDiff | Restoring Vision in Adverse Weather Conditions with Patch-Based Denoising Diffusion Models Ozan Özdenizci, Robert Legenstein |
TPAMI 2023 |
Paper/Code |
Release | Method | Title | Pub. | Link |
---|---|---|---|---|
2024/01 | CFWD | Low-light Image Enhancement via CLIP-Fourier Guided Wavelet Diffusion Minglong Xue, Jinhong He, Yanyi He, Zhipu Liu, Wenhai Wang, Mingliang Zhou |
arXiv 2024 |
Paper/Code |
2023/12 | L2DM | L2DM: A Diffusion Model for Low-Light Image Enhancement Lv, Xingguo and Dong, Xingbo and Jin, Zhe and Zhang, Hui and Song, Siyi and Li, Xuejun |
PRCV 2023 |
Paper/Code |
2023/11 | Reti-Diff | Reti-Diff: Illumination Degradation Image Restoration with Retinex-based Latent Diffusion Model Chunming He, Chengyu Fang, Yulun Zhang, Kai Li, Longxiang Tang, Chenyu You, Fengyang Xiao, Zhenhua Guo, Xiu Li |
arXiv 2023 |
Paper/Code |
2023/10 | GASD | Global Structure-Aware Diffusion Process for Low-Light Image Enhancement Jinhui Hou, Zhiyu Zhu, Junhui Hou, Hui Liu, Huanqiang Zeng, Hui Yuan |
NIPS 2023 |
Paper/Code |
2023/10 | LLDE | LLDE: Enhancing Low-Light Images with Diffusion Model Xin Peng Oo, Chee Seng Chan |
ICIP 2023 |
Paper/Code |
2023/09 | - | Bootstrap Diffusion Model Curve Estimation for High Resolution Low-Light Image Enhancement Jiancheng Huang, Yifan Liu, Shifeng Chen |
PRICAI 2023 |
Paper/ |
2023/08 | ExposureDiffusion | ExposureDiffusion: Learning to Expose for Low-light Image Enhancement Yufei Wang, Yi Yu, Wenhan Yang, Lanqing Guo, Lap-Pui Chau, Alex C. Kot, Bihan Wen |
ICCV 2023 |
Paper/Code |
2023/08 | Diff-Retinex | Diff-Retinex: Rethinking Low-light Image Enhancement with A Generative Diffusion Model Xunpeng Yi, Han Xu, Hao Zhang, Linfeng Tang, Jiayi Ma |
ICCV 2023 |
Paper/ |
2023/08 | CLE Diffusion | CLE Diffusion: Controllable Light Enhancement Diffusion Model Yuyang Yin, Dejia Xu, Chuangchuang Tan, Ping Liu, Yao Zhao, Yunchao Wei |
MM 23 |
Paper/Code |
2023/07 | LLDiffusion | LLDiffusion: Learning Degradation Representations in Diffusion Models for Low-Light Image Enhancement Tao Wang, Kaihao Zhang, Ziqian Shao, Wenhan Luo, Bjorn Stenger, Tae-Kyun Kim, Wei Liu, Hongdong Li |
arXiv 2023 |
Paper/Code |
2023/07 | DiffLIE | DiffLIE: Low-Light Image Enhancment based on Deep Diffusion Model Guanyu Wu; Cheng. Jin |
ISCTIS 2023 |
Paper/ |
2023/06 | - | Diffusion Model Based Low-Light Image Enhancement for Space Satellite Yiman Zhu, Lu Wang, Jingyi Yuan, Yu Guo |
arXiv 2023 |
Paper/ |
2023/05 | PyDiff | Pyramid Diffusion Models For Low-light Image Enhancement Dewei Zhou, Zongxin Yang, Yi Yang |
IJCAI 2023 |
Paper/Code |
2023/03 | LPDM | Denoising Diffusion Post-Processing for Low-Light Image Enhancement Savvas Panagiotou, Anna S. Bosman |
arXiv 2023 |
Paper/Code |
2023/03 | DiD | Diffusion in the Dark: A Diffusion Model for Low-Light Text Recognition Cindy M. Nguyen, Eric R. Chan, Alexander W. Bergman, Gordon Wetzstein |
WACV 2024 |
Paper/Code |
2023/01 | DiffLL | Low-Light Image Enhancement with Wavelet-based Diffusion Models Hai Jiang, Ao Luo, Songchen Han, Haoqiang Fan, Shuaicheng Liu |
TOG 2023 |
Paper/Code |
Release | Method | Title | Pub. | Link |
---|---|---|---|---|
2023/06 | FusionDiff | FusionDiff: Multi-focus image fusion using denoising diffusion probabilistic models Mining Li, Ronghao Pei, Tianyou Zheng, Yang Zhang, Weiwei Fu |
ESWA 2024 |
Paper/Code |
2023/03 | DDFM | DDFM: Denoising Diffusion Model for Multi-Modality Image Fusion Zixiang Zhao, Haowen Bai, Yuanzhi Zhu, Jiangshe Zhang, Shuang Xu, Yulun Zhang, Kai Zhang, Deyu Meng, Radu Timofte, Luc Van Gool |
ICCV 2023 |
Paper/Code |
2023/01 | Dif-Fusion | Dif-Fusion: Towards High Color Fidelity in Infrared and Visible Image Fusion with Diffusion Models Jun Yue, Leyuan Fang, Shaobo Xia, Yue Deng, Jiayi Ma |
TIP 2023 |
Paper/Code |
Release | Method | Title | Pub. | Link |
---|---|---|---|---|
2022/07 | AdaDiff | Adaptive Diffusion Priors for Accelerated MRI Reconstruction Alper Güngör, Salman UH Dar, Şaban Öztürk, Yilmaz Korkmaz, Gokberk Elmas, Muzaffer Özbey, Tolga Çukur |
MedIA 2023 |
Paper/Code |
2021/10 | Score-MRI | Score-based diffusion models for accelerated MRI Hyungjin Chung, Jong Chul Ye |
MedIA 2022 |
Paper/Code |
2021/08 | CSGM | Robust Compressed Sensing MRI with Deep Generative Priors Alper Güngör, Salman UH Dar, Şaban Öztürk, Yilmaz Korkmaz, Gokberk Elmas, Muzaffer Özbey, Tolga Çukur |
NIPS 2021 |
Paper/Code |
Release | Method | Title | Pub. | Link |
---|---|---|---|---|
2022/11 | DOLCE | DOLCE: A Model-Based Probabilistic Diffusion Framework for Limited-Angle CT Reconstruction Jiaming Liu, Rushil Anirudh, Jayaraman J. Thiagarajan, Stewart He, K. Aditya Mohan, Ulugbek S. Kamilov, Hyojin Kim |
ICCV 2023 |
Paper/Code |
Release | Method | Title | Pub. | Link |
---|---|---|---|---|
2023/04 | FGDM | Zero-shot Medical Image Translation via Frequency-Guided Diffusion Models Yunxiang Li, Hua-Chieh Shao, Xiao Liang, Liyuan Chen, Ruiqi Li, Steve Jiang, Jing Wang, You Zhang |
TMI 2023 |
Paper/ |
2022/09 | - | Conversion Between CT and MRI Images Using Diffusion and Score-Matching Models Qing Lyu, Ge Wang |
arXiv 2022 |
Paper/ |
2022/07 | UMM-CSGM | A Novel Unified Conditional Score-based Generative Framework for Multi-modal Medical Image Completion Xiangxi Meng, Yuning Gu, Yongsheng Pan, Nizhuan Wang, Peng Xue, Mengkang Lu, Xuming He, Yiqiang Zhan, Dinggang Shen |
arXiv 2022 |
Paper/ |
Release | Method | Title | Pub. | Link |
---|---|---|---|---|
2024/02 | - | Dehazing Ultrasound using Diffusion Models Tristan S.W. Stevens, Faik C. Meral, Jason Yu, Iason Z. Apostolakis, Jean-Luc Robert, Ruud J.G. Van Sloun |
TMI 2024 |
Paper/ |
2022/09 | PET-DDM | PET image denoising based on denoising diffusion probabilistic models Kuang Gong, Keith A. Johnson, Georges El Fakhri, Quanzheng Li, Tinsu Pan |
Eur. J. Nucl. Med. Mol. Imaging 2023 |
Paper/ |
2022/01 | DenoOCT-DDPM | Unsupervised Denoising of Retinal OCT with Diffusion Probabilistic Model Dewei Hu, Yuankai K. Tao, Ipek Oguz |
SPIE 2022 |
Paper/Code |
Release | Method | Title | Pub. | Link |
---|---|---|---|---|
2023/10 | EDiffSR | EDiffSR: An Efficient Diffusion Probabilistic Model for Remote Sensing Image Super-Resolution Yi Xiao, Qiangqiang Yuan, Kui Jiang, Jiang He, Xianyu Jin, Liangpei Zhang |
TGRS 2024 |
Paper/Code |
2023/09 | RSDiff | RSDiff: Remote Sensing Image Generation from Text Using Diffusion Model Ahmad Sebaq, Mohamed ElHelw |
arXiv 2023 |
Paper/ |
2023/08 | ARDD-Net | Remote Sensing Image Dehazing Using Adaptive Region-Based Diffusion Models Y Huang, S Xiong |
LGRS 2023 |
Paper/ |
2022/09 | PSSR | Diffusion Model with Detail Complement for Super-Resolution of Remote Sensing Liu, Jinzhe and Yuan, Zhiqiang and Pan, Zhaoying and Fu, Yiqun and Liu, Li and Lu, Bin |
Remote Sensing 2022 |
Paper/ |
Release | Method | Title | Pub. | Link |
---|---|---|---|---|
2023/07 | DDPM-Fus | Hyperspectral and Multispectral Image Fusion Using the Conditional Denoising Diffusion Probabilistic Model Shuaikai Shi, Lijun Zhang, Jie Chen |
arXiv 2023 |
Paper/Code |
2023/07 | - | A Noise-Model-Free Hyperspectral Image Denoising Method Based on Diffusion Model Deng, Keli and Jiang, Zhongshun and Qian, Qipeng and Qiu, Yi and Qian, Yuntao |
IGASS 2023 |
Paper/ |
2023/07 | R2H-CCD | R2H-CCD: Hyperspectral Imagery Generation from RGB Images Based on Conditional Cascade Diffusion Probabilistic Models Zhang, Lei and Luo, Xiaoyan and Li, Sen and Shi, Xiaofeng |
IGASS 2023 |
Paper/ |
2023/03 | DDS2M | DDS2M: Self-Supervised Denoising Diffusion Spatio-Spectral Model for Hyperspectral Image Restoration Yuchun Miao, Lefei Zhang, Liangpei Zhang, Dacheng Tao |
ICCV 2023 |
Paper/Code |
2023/01 | HSR-Diff | HSR-Diff:Hyperspectral Image Super-Resolution via Conditional Diffusion Models Chanyue Wu, Dong Wang, Hanyu Mao, Ying Li |
ICCV 2023 |
Paper/ |
Release | Method | Title | Pub. | Link |
---|---|---|---|---|
2023/07 | - | Unsupervised SAR Despeckling Based on Diffusion Model Xiao, Siyao and Huang, Libing and Zhang, Shunsheng |
IGASS 2023 |
Paper/ |
2023/08 | - | Diffusion Models for Interferometric Satellite Aperture Radar Alexandre Tuel, Thomas Kerdreux, Claudia Hulbert, Bertrand Rouet-Leduc |
arXiv 2023 |
Paper/Code |
2023/06 | - | SAR Despeckling using a Denoising Diffusion Probabilistic Model Malsha V. Perera, Nithin Gopalakrishnan Nair, Wele Gedara Chaminda Bandara, Vishal M. Patel |
LGRS 2023 |
Paper/Code |
Release | Method | Title | Pub. | Link |
---|---|---|---|---|
2023/07 | - | Improved Flood Insights: Diffusion-Based SAR to EO Image Translation Minseok Seo, Youngtack Oh, Doyi Kim, Dongmin Kang, Yeji Choi |
arXiv 2023 |
Paper/ |
2023/04 | - | Cloud Removal in Remote Sensing Using Sequential-Based Diffusion Models Zhao, Xiaohu and Jia, Kebin |
Remote Sensing 2023 |
Paper/ |
2023/04 | DDRF | DDRF: Denoising Diffusion Model for Remote Sensing Image Fusion ZiHan Cao, ShiQi Cao, Xiao Wu, JunMing Hou, Ran Ran, Liang-Jian Deng |
arXiv 2023 |
Paper/ |
2023/03 | DDPM-CR | Denoising Diffusion Probabilistic Feature-Based Network for Cloud Removal in Sentinel-2 Imagery Jing, Ran and Duan, Fuzhou and Lu, Fengxian and Zhang, Miao and Zhao, Wenji |
Remote Sensing 2023 |
Paper/ |
Release | Method | Title | Pub. | Link |
---|---|---|---|---|
2023/03 | LDMVFI | LDMVFI: Video Frame Interpolation with Latent Diffusion Models Duolikun Danier, Fan Zhang, David Bull |
arXiv 2023 |
Paper/Code |
2022/06 | RaMViD | Diffusion Models for Video Prediction and Infilling Tobias Höppe, Arash Mehrjou, Stefan Bauer, Didrik Nielsen, Andrea Dittadi |
TMLR 2022 |
Paper/ |
2022/05 | MCVD | MCVD: Masked Conditional Video Diffusion for Prediction, Generation, and Interpolation Vikram Voleti, Alexia Jolicoeur-Martineau, Christopher Pal |
NIPS 2022 |
Paper/Code |
2022/03 | RVD | Diffusion Probabilistic Modeling for Video Generation Ruihan Yang, Prakhar Srivastava, Stephan Mandt |
Entropy 2023 |
Paper/Code |
Release | Method | Title | Pub. | Link |
---|---|---|---|---|
2024/03 | SATeCo | Learning Spatial Adaptation and Temporal Coherence in Diffusion Models for Video Super-Resolution Zhikai Chen, Fuchen Long, Zhaofan Qiu, Ting Yao, Wengang Zhou, Jiebo Luo, Tao Mei |
CVPR 2024 |
Paper/ |
2024/01 | - | Inflation with Diffusion: Efficient Temporal Adaptation for Text-to-Video Super-Resolution Xin Yuan, Jinoo Baek, Keyang Xu, Omer Tov, Hongliang Fei |
WACV 2024 |
Paper/ |
2023/09 | LAVIE | LAVIE: High-Quality Video Generation with Cascaded Latent Diffusion Models Yaohui Wang, Xinyuan Chen, Xin Ma, Shangchen Zhou, Ziqi Huang, Yi Wang, Ceyuan Yang, Yinan He, Jiashuo Yu, Peiqing Yang, Yuwei Guo, Tianxing Wu, Chenyang Si, Yuming Jiang, Cunjian Chen, Chen Change Loy, Bo Dai, Dahua Lin, Yu Qiao, Ziwei Liu |
arXiv 2023 |
Paper/Code |
2023/05 | PYoCo | Preserve Your Own Correlation: A Noise Prior for Video Diffusion Models Songwei Ge, Seungjun Nah, Guilin Liu, Tyler Poon, Andrew Tao, Bryan Catanzaro, David Jacobs, Jia-Bin Huang, Ming-Yu Liu, Yogesh Balaji |
ICCV 2023 |
Paper/Demo |
2023/04 | - | Align your Latents: High-Resolution Video Synthesis with Latent Diffusion Models Andreas Blattmann, Robin Rombach, Huan Ling, Tim Dockhorn, Seung Wook Kim, Sanja Fidler, Karsten Kreis |
CVPR 2023 |
Paper/Demo |
Release | Method | Title | Pub. | Link |
---|---|---|---|---|
2024/03 | DiffTTA | Genuine Knowledge from Practice: Diffusion Test-Time Adaptation for Video Adverse Weather Removal Yijun Yang, Hongtao Wu, Angelica I. Aviles-Rivero, Yulun Zhang, Jing Qin, Lei Zhu |
CVPR 2024 |
Paper/Code |
Diffusion Models in Low-Level Vision: A Survey
arXiv 2024. [Paper]
Jun. 2024
Diffusion Models Meet Remote Sensing: Principles, Methods, and Perspectives
arXiv 2024. [Paper]
Apr. 2024
Diffusion Models, Image Super-Resolution And Everything: A Survey
arXiv 2024. [Paper]
Jan. 2024
State of the Art on Diffusion Models for Visual Computing
arXiv 2023. [Paper]
Oct. 2023
Diffusion Models for Image Restoration and Enhancement -- A Comprehensive Survey.
arXiv 2023. [Paper]
Aug. 2023
Survey on Diverse Image Inpainting using Diffusion Models
PCEMS 2023. [Paper]
Jun. 2023
Diffusion Models for Medical Image Analysis: A Comprehensive Survey
Medical Image Analysis 2023. [Paper]
Nov. 2022
Diffusion Models in Vision: A Survey
TPAMI 2023. [Paper]
Sep. 2022
Diffusion Models: A Comprehensive Survey of Methods and Applications
ACM Computing Surveys 2023. [Paper]
Sep. 2022
Due to space limitations, we provide a summary of commonly used datasets for several classical natural low-level vision tasks here, including their scales, sources, modalities, and remarks. Clicking on the dataset will redirect you to its download link.
Tasks | Datasets | Scales | Sources | Modalities | Remarks |
---|---|---|---|---|---|
SR | BSD500 | 500 | TPAMI 2010 | Syn | A synthetic benchmark that is initially designed for object contour detection. |
SR | Set14 | 14 | TPAMI 2015 | Syn | Commonly utilized for testing performance of super-resolution algorithms. |
SR | Manga109 | 109 | MTAP 2015 | Syn | Compiled mainly for academic research on Japanese manga media processing. |
SR | General100 | 100 | ECCV 2016 | Syn | Synthesized images in uncompressed BMP format covering various scales. |
SR | DIV2K | 900/100 | NTIRE 2018 | Real | A commonly-used dataset with diverse scenarios and realistic degradations. |
SR | Flickr1024 | 1024 | ICCVW 2019 | Syn | A large-scale stereo image dataset with high-quality pairs and diverse scenarios. |
SR | Urban100 | 100 | CVPR 2019 | Syn | Sourced from urban environments: city streets, buildings, and urban landscapes. |
SR | DRealSR | 31970 | ECCV 2020 | Real | Benchmarks captured by DSLR cameras, circumventing simulated degradation. |
Deblur | GoPro | 2103/1111 | CVPR 2017 | Syn | Acquired by high-speed cameras for video quality assessment and restoration. |
Deblur | HIDE | 8422 | ICCV 2019 | Syn | Cover long-distance and short-distance scenarios degraded by motion blur. |
Deblur | REDS | 270/30 | NTIRE 2019 | Real | Contain 300 video sequences with dynamic duration and varied resolutions. |
Deblur | BSD | 80/20 | ECCV 2020 | Real | Comprise more scenes and use the proposed beam-splitter acquisition system. |
Deblur | RealBlur | 3758/980 | ECCV 2020 | Real | Cover common instances of motion blur, captured in raw and JPEG formats. |
Dehaze | I-Haze | 35 | NTIRE 2018 | Real | Indoor dataset with real haze for objective image dehazing and evaluation. |
Dehaze | O-Haze | 45 | NTIRE 2018 | Real | Outdoor dataset with real haze for objective image dehazing and evaluation. |
Dehaze | Dense-Haze | 33 | ICIP 2019 | Real | Real-world dataset with dense haze for robust single image dehazing methods. |
Dehaze | RESIDE | 13000/990 | TIP 2019 | Syn+Real | Divided into five subsets to highlight diverse sources and heterogeneous contents. |
Dehaze | NH-Haze | 55 | CVRPW 2020 | Real | The first non-homogeneous dehazing dataset with realistic haze distribution. |
Dehaze | Haze-4K | 4000 | MM 2021 | Syn | A large-scale synthetic dataset for image dehazing with varing distributions. |
LLIE | MIT-Fivek | 4500/500 | CVPR 2011 | Syn | A curated dataset of RAW photos adjusted by skilled retouchers for visual appeal. |
LLIE | LOLv1 | 485/15 | BMVC 2018 | Real | The first dataset with image pairs from real scenarios for low-light enhancement. |
LLIE | SID | 5094 | CVPR 2018 | Real | A dataset of raw short-exposure images with their long-exposure reference images. |
LLIE | SICE | 589 | TIP 2018 | Syn | A large-scale multi-exposure image dataset with complex illumination conditions. |
LLIE | ExDark | 7363 | CVIU 2019 | Real | Collected in low-light scenarios with 12 classes and instance-level annotations. |
LLIE | LOLv2-Real | 689/100 | TIP 2021 | Real | A three-step shooting strategy is used to eliminate intra-pair image misalignments. |
LLIE | LOLv2-Syn | 900/100 | TIP 2021 | Syn | Synthetic dark images mimic real low-light photography via histogram analysis. |
LLIE | SDSD-Indoor | 62/6 | ICCV 2021 | Real | Indoor dataset collected from dynamic scenes under varying lighting conditions. |
LLIE | SDSD-Outdoor | 116/10 | ICCV 2021 | Real | Outdoor dataset collected from dynamic scenes under varying lighting conditions. |
Derain | Rain100H | 1800/100 | CVPR 2017 | Syn | Comprise synthetic datasets with five types of rain streaks for rain removal. |
Derain | RainDrop | 861/239 | CVPR 2018 | Syn | Image pairs with raindrop degradation, captured using the setup of dual glasses. |
Derain | SPA-Data | 638492/1000 | CVPR 2019 | Real | Design a semi-automatic method to generate clean images from real rain streaks. |
Derain | MPID | 3961/419 | CVPR 2019 | Syn+Real | A large-scale benchmark that focuses on driving and surveillance scenarios. |
Derain | RainCityscapes | 9432/1188 | CVPR 2019 | Syn | A famous rain removal dataset with paired depth maps for outdoor scenarios. |
Derain | RainDS | 3450/900 | CVPR 2021 | Syn+Real | A hybrid dataset with both real and synthesized data under diverse scenarios. |
Derain | RainDirection | 2920/430 | ICCV 2021 | Syn | A large-scale synthetic rainy dataset with directional labels in the training phase. |
Derain | GT-RAIN | 28217/2100 | ECCV 2022 | Real | The first paired derain dataset with real data by controlling non-rain variations. |
Desnow | Snow100k | 100000 | TIP 2018 | Syn+Real | A large-scale dataset with over 1k real-world images degraded by heavy snow. |
Desnow | SRRS | 16000 | ECCV 2020 | Syn+Real | A hybrid snow dataset with 15k synthesized images and 1k real-world images. |
Desnow | CSD | 10000 | ICCV 2021 | Syn | A large-scale desnowing dataset to comprehensively simulate snow scenarios. |
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Awesome-Diffusion-Models-in-Medical-Imaging: Diffusion Models in Medical Imaging