c-yn / ConvIR

Revitalizing Convolutional Network for Image Restoration
MIT License
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Revitalizing Convolutional Network for Image Restoration

The official pytorch implementation of the paper Revitalizing Convolutional Network for Image Restoration

Yuning Cui, Wenqi Ren, Xiaochun Cao, Alois Knoll

News

All resulting images and pre-trained models are available in the provided links.

07/22/2024 We release the code for dehazing (ITS/OTS), desnowing, deraining, and motion deblurring.

Pretrained models

gdrive, 百度网盘

Installation

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 ..

Training and Evaluation

Please refer to respective directories.

Results

Visualization Results: gdrive, 百度网盘

Model Parameters FLOPs
ConvIR-S (small) 5.53M 42.1G
ConvIR-B (base) 8.63M 71.22G
ConvIR-L (large) 14.83M 129.34G
Task Dataset PSNR SSIM
Image Dehazing SOTS-Indoor 41.53/42.72 0.996/0.997
SOTS-Outdoor 37.95/39.42 0.994/0.996
Haze4K 33.36/34.15/34.50 0.99/0.99/0.99
Dense-Haze 17.45/16.86 0.648/0.621
NH-HAZE 20.65/20.66 0.807/0.802
O-HAZE 25.25/25.36 0.784/0.780
I-HAZE 21.95/22.44 0.888/0.887
SateHaze-1k-Thin/Moderate/Thick 25.11/26.79/22.65 0.978/0.978/0.950
NHR 28.85/29.49 0.981/0.983
GTA5 31.68/31.83 0.917/0.921
Image Desnowing CSD 38.43/39.10 0.99/0.99
SRRS 32.25/32.39 0.98/0.98
Snow100K 33.79/33.92 0.95/0.96
Image Deraining Test100 31.40 0.919
Test2800 33.73 0.937
Defocus Deblurring DPDD 26.06/26.16/26.36 0.810/0.814/0.820
Motion Deblurring GoPro 33.28 0.963
RSBlur 34.06 0.868

Citation

@article{cui2024revitalizing,
  title={Revitalizing Convolutional Network for Image Restoration},
  author={Cui, Yuning and Ren, Wenqi and Cao, Xiaochun and Knoll, Alois},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year={2024},
  publisher={IEEE}
}

@inproceedings{cui2023irnext,
  title={IRNeXt: Rethinking Convolutional Network Design for Image Restoration},
  author={Cui, Yuning and Ren, Wenqi and Yang, Sining and Cao, Xiaochun and Knoll, Alois},
  booktitle={International Conference on Machine Learning},
  pages={6545--6564},
  year={2023},
  organization={PMLR}
}

Contact

Should you have any problem, please contact Yuning Cui.