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ai4-metadata.yml
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metadata_version: 2.0.0
title: smartbay-dover-vqa
summary: "Implementation of DOVER VQA from ICCV 2023, Official Code for paper "Exploring Video Quality Assessment on User Generated Contents from Aesthetic and Technical Perspectives" (Wu, Haoning and Zhang, Erli and Liao, Liang and Chen, Chaofeng and Hou, Jingwen Hou and Wang, Annan and Sun, Wenxiu Sun and Yan, Qiong and Lin, Weisi)"
description: |-
smartbay_dover_vqa is an application using the DEEPaaS API.
Implementation of DOVER VQA from ICCV 2023, Official Code for paper "Exploring Video Quality Assessment on User Generated Contents from Aesthetic and Technical Perspectives" (Wu, Haoning and Zhang, Erli and Liao, Liang and Chen, Chaofeng and Hou, Jingwen Hou and Wang, Annan and Sun, Wenxiu Sun and Yan, Qiong and Lin, Weisi)
# doi: http://add-some-DOI-url.com
dates:
created: 2024-10-25
updated: 2024-10-25
links:
ai4_template: ai4-template/2.1.5
source_code: https://github.com/ai4os-hub/smartbay-dover-vqa
docker_image: ai4oshub/smartbay-dover-vqa
# documentation: http://add-some-documentation.com
# dataset: http://add-some-url-pointing-to-your-dataset.com
# weights: http://add-some-weights-url.com
# citation: http://add-some-DOI-url.com
# base_model: http://add-some-link-to-another-model.com
#tags: # required property, add user-defined tags that you consider relevant
# - deep learning
#tasks: # required property, uncomment together with relevant items
# - Computer Vision
# - Natural Language Processing
# - Time Series
# - Recommender Systems
# - Anomaly Detection
# - Regression
# - Classification
# - Clustering
# - Dimensionality Reduction
# - Generative Models
# - Graph Neural Networks
# - Optimization
# - Reinforcement Learning
# - Transfer Learning
# - Uncertainty Estimation
# - Other
#categories: # required property, uncomment together with relevant items
# - AI4 trainable
# - AI4 pre trained
# - AI4 inference
# - AI4 tools
#libraries: # required property, uncomment together with relevant items
# - TensorFlow
# - PyTorch
# - Keras
# - Scikit-learn
# - XGBoost
# - LightGBM
# - CatBoost
# - Other
#data-type: # optional, uncomment together with relevant items
# - Image
# - Text
# - Time Series
# - Tabular
# - Graph
# - Audio
# - Video
# - Other