/CSNet

Hybrid frequency modulation network for image restoration

Primary LanguagePythonMIT LicenseMIT

Hybrid Frequency Modulation Network for Image Restoration [IJCAI'24]

supplementary material, visual results, and models can be found here

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 ..

Computational complexity: for dehazing 41.19 GFLOPs, 4.27M

Citation

@inproceedings{cui2024hybrid,
  title={Hybrid Frequency Modulation Network for Image Restoration},
  author={Cui, Yuning and Liu, Mingyu and Ren, Wenqi and Knoll, Alois},
  booktitle={International Joint Conference on Artificial Intelligence},
  year={2024}
}

Contact

Should you have any question, please contact Yuning Cui.