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Omniscient Video Super-Resolution

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Omniscient Video Super-Resolution

This is the official code of OVSR (Omniscient Video Super-Resolution, ICCV 2021). This work is based on PFNL.

Datasets

Please refer to PFNL for the datasets (train, eval and test). Please modify the datapath in ./data/*.txt according to your machine.

Pre-Trained Models

Download the pre-trained models from mainland China with password: inub, or elsewhere.

Code

It should be easy to use train.sh or main.py for training or testing, note to change the hyper-parameters in options/ovsr.yml .

Environment

  • Python >= 3.6
  • PyTorch, tested on 1.9, but should be fine when >=1.6

Citation

If you find our code or datasets helpful, please consider citing our related works.

@InProceedings{Yi_2021_ICCV_OVSR,
    author    = {Yi, Peng and Wang, Zhongyuan and Jiang, Kui and Jiang, Junjun and Lu, Tao and Tian, Xin and Ma, Jiayi},
    title     = {Omniscient Video Super-Resolution},
    booktitle = {IEEE/CVF International Conference on Computer Vision (ICCV)},
    month     = {October},
    year      = {2021},
    pages     = {4429-4438}
}

@ARTICLE{MSHPFNL,
  author={Yi, Peng and Wang, Zhongyuan and Jiang, Kui and Jiang, Junjun and Lu, Tao and Ma, Jiayi},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence}, 
  title={A Progressive Fusion Generative Adversarial Network for Realistic and Consistent Video Super-Resolution}, 
  year={2020},
  volume={},
  number={},
  pages={},
  doi={10.1109/TPAMI.2020.3042298}
}

Contact

If you have questions or suggestions, please open an issue here or send an email to yipeng@whu.edu.cn.

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Omniscient Video Super-Resolution

License:Apache License 2.0


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