Yuning Cui, Alois Knoll
The project is built with PyTorch 3.8, PyTorch 1.8.1. CUDA 10.2, cuDNN 7.6.5 For installing, follow these instructions:
conda install pytorch=1.8.1 torchvision=0.9.1 -c pytorch
pip install tensorboard einops scikit-image pytorch_msssim opencv-python
Install warmup scheduler:
cd pytorch-gradual-warmup-lr/
python setup.py install
cd ..
Pre-trained models here
| Task | Dataset | PSNR | SSIM |
|---|---|---|---|
| Image Dehazing | ITS | 41.36 | 0.997 |
| OTS | 38.39 | 0.995 | |
| Dense-Haze | 16.70 | 0.607 | |
| NH-HAZE | 20.51 | 0.801 | |
| O-HAZE | 25.79 | 0.94 | |
| NH-HAZE2 | 21.63 | 0.841 | |
| NHR | 28.08 | 0.978 | |
| Image Desnowing | CSD | 38.09 | 0.99 |
| SRRS | 31.97 | 0.98 | |
| Snow100K | 33.70 | 0.95 |
If you find this project useful for your research, please consider citing:
@article{cui2024dual,
title={Dual-domain strip attention for image restoration},
author={Cui, Yuning and Knoll, Alois},
journal={Neural Networks},
volume={171},
pages={429--439},
year={2024},
publisher={Elsevier}
}
Should you have any question, please contact Yuning Cui.