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TDAN: Temporally-Deformable Alignment Network for Video Super-Resolution, CVPR 2020
| Date | Stars |
|---|---|
| 2026-07-24 | 418 |
| 2026-07-25 | 418 |
| 2026-07-28 | 418 |
| 2026-07-30 | 418 |
| 2026-08-06 | 418 |
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# TDAN-CVPR 2020 （Keep Update）
This is the official Pytorch implementation of *TDAN: Temporally-Deformable Alignment Network for Video Super-Resolution*.
#### [Paper](https://openaccess.thecvf.com/content_CVPR_2020/papers/Tian_TDAN_Temporally-Deformable_Alignment_Network_for_Video_Super-Resolution_CVPR_2020_paper.pdf) | [Demo Video](https://www.youtube.com/watch?v=eZExENE50I0)
[](https://www.youtube.com/watch?v=eZExENE50I0)
## Usage
Main dependencies: Python 3.6 and Pytorch-0.3.1 (https://pytorch.org/get-started/previous-versions/)
```bash
$ git clone https://github.com/YapengTian/TDAN-VSR
$ compile deformable convolution functions (may be optional): bash make.sh
$ pip install -r requirements
$ python eval.py -t test_dataset_path
```
### Citation
If you find the code helpful in your resarch or work, please cite our paper:
```BibTex
@article{tian2018tdan,
title={Tdan: Temporally deformable alignment network for video super-resolution},
author={Tian, Yapeng and Zhang, Yulun and Fu, Yun and Xu, Chenliang},
journal={arXiv preprint arXiv:1812.02898},
year={2018}
}
@InProceedings{tian2020tdan,
author={Tian, Yapeng and Zhang, Yulun and Fu, Yun and Xu, Chenliang},
title={TDAN: Temporally-Deformable Alignment Network for Video Super-Resolution},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
```
### Resources for deformanble convolution in video restoration
TDAN present a promising framework for deformable alignment, which is shown very effective in video restoration tasks. We are super excited that our works has inspired many well-performing methods. We list a few of them for your potential reference:
* EDVR: Video restoration with enhanced deformable convolutional networks: [paper](https://arxiv.org/abs/1905.02716), [code](https://github.com/xinntao/EDVR)
* Zooming Slow-Mo: Fast and Accurate One-Stage Space-Time VideoSuper-Resolution: [paper](https://arxiv.org/abs/2002.11616), [code](https://github.com/Mukosame/Zooming-Slow-Mo-CVPR-2020)
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Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:d2c1c73888c22644, topic:super-resolution, desc:super resolution, readme:super resolution
matched fp:d2c1c73888c22644, topic:pytorch