CPGA

The dataset and code of the paper "CPGA: Coding Priors-Guided Aggregation Network for Compressed Video Quality Enhancement".

Requirements

CUDA==11.6 Python==3.7 Pytorch==1.13

1.1 Environment

conda create -n cpga python=3.7 -y && conda activate cpga

git clone --depth=1 https://github.com/VQE-CPGA/CPGA && cd VQE-CPGA/CPGA/

# given CUDA 11.6
python -m pip install torch==1.13.1+cu116 torchvision==0.14.1+cu116 torchaudio==0.13.1 --extra-index-url https://download.pytorch.org/whl/cu116

python -m pip install tqdm lmdb pyyaml opencv-python scikit-image

1.2 DCNv2

cd ops/dcn/
bash build.sh

Check if DCNv2 work (optional)

python simple_check.py

1.3 VCP dataset

Download raw and compressed videos

Please check BaiduPan,Code [qix5].

Edit YML

You need to edit option_CPGA_vcp_#_QP#.yml file.

Generate LMDB

The LMDB generation for speeding up IO during training.

python create_vcp.py --opt_path option_CPGA_vcp_#_QP#.yml

Finally, the VCP dataset root will be sym-linked to the folder ./data/ automatically.

1.4 Test dataset

We use the JCT-VC testing dataset in JCT-VC. Download raw and compressed videos BaiduPan,Code [qix5].

Train

python train_CPGA.py --opt_path ./config/option_CPGA_vcp_LDB_22.yml

Test

python test_CPGA.py --opt_path ./config/option_CPGA_vcp_LDB_22.yml

Citation

If this repository is helpful to your research, please cite our paper:

@inproceedings{zhu2024cpga,
  title={CPGA: Coding Priors-Guided Aggregation Network for Compressed Video Quality Enhancement},
  author={Zhu, Qiang and Hao, Jinhua and Ding, Yukang and Liu, Yu and Mo, Qiao and Sun, Ming and Zhou, Chao and Zhu, Shuyuan},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages={2964--2974},
  year={2024}
}
@article{zhu2024deep,
  title={Deep Compressed Video Super-Resolution With Guidance of Coding Priors},
  author={Qiang Zhu, Feiyu Chen, Yu Liu, Shuyuan Zhu, Bing Zeng},
  journal={ IEEE Transactions on Broadcasting },
  volume={70},
  issue={2},
  pages={505-515},
  year={2024}
  publisher={IEEE},
  doi={10.1109/TBC.2024.3394291}
}
@article{zhu2024compressed,
  title={Compressed Video Quality Enhancement with Temporal Group Alignment and Fusion},
  author={Qiang, Zhu and Yajun, Qiu and Yu, Liu and Shuyuan, Zhu and Bing, Zeng},
  journal={IEEE Signal Processing Letters},
  year={2024},
  publisher={IEEE},
  doi={10.1109/LSP.2024.3407536}
}
@inproceedings{mo2025oapt,
  title={OAPT: Offset-Aware Partition Transformer for Double JPEG Artifacts Removal},
  author={Mo, Qiao and Ding, Yukang and Hao, Jinhua and Zhu, Qiang and Sun, Ming and Zhou, Chao and Chen, Feiyu and Zhu, Shuyuan},
  booktitle={European Conference on Computer Vision},
  pages={38--56},
  year={2025},
  organization={Springer}
}

We adopt Apache License v2.0. For other licenses, please refer to DCNv2.