Awesome
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.