Hongming Chen, Xiang Chen, Chen Wu, Zhuoran Zheng, Jinshan Pan, and Xianping Fu
Type the command:
pip install -r requirements.txt
(The datasets are hosted on both Google Drive and BaiduPan)
| Download Link | Description |
|---|---|
| Google Drive / Baidu Netdisk | A total of 12,500 pairs for training and 500 pairs for testing. |
- Please download the corresponding datasets and put them in the folder
data/. - Follow the instructions below to begin training our model.
python train.py
- Follow the instructions below to begin testing our model.
python test.py
Run the script then you can find the output visual results in the folder output/.
The PSNR, SSIM and MSE results are computed by using this Python Code.
| Method | Download Link |
|---|---|
| LPNet | Google Drive / Baidu Netdisk |
| JORDER-E | Google Drive / Baidu Netdisk |
| RCDNet | Google Drive / Baidu Netdisk |
| SPDNet | Google Drive / Baidu Netdisk |
| IDT | Google Drive / Baidu Netdisk |
| Restormer | Google Drive / Baidu Netdisk |
| DRSformer | Google Drive / Baidu Netdisk |
| UDR-S2Former | Google Drive / Baidu Netdisk |
| UDR-Mixer | Google Drive / Baidu Netdisk |
If you find this project useful in your research, please consider citing:
@article{chen2024towards,
title={Towards Ultra-High-Definition Image Deraining: A Benchmark and An Efficient Method},
author={Chen, Hongming and Chen, Xiang and Wu, Chen and Zheng, Zhuoran and Pan, Jinshan and Fu, Xianping},
journal={arXiv preprint arXiv:2405.17074},
year={2024}
}
Please only use the dataset for research purposes.
If you have any questions, please feel free to reach me out at chenxiang@njust.edu.cn