Discrepant Untrained Network Priors

Official PyTorch implementation of the paper Self-Supervised Low-Light Image Enhancement Using Discrepant Untrained Network Priors published in IEEE TCSVT 2022.

Paper | Supplementary material

Dependencies and Installation

1. Create conda environment

conda create --name drp python=3.6
conda activate drp

2. Clone repo

git clone https://github.com/sherrycattt/discrepant-untrained-nn-priors.git

3. Install dependencies

cd discrepant-untrained-nn-priors
pip install -r requirements.txt

Run

Specify the input path input_path, the output directory output_dir, and other hyper-parameters. Then run

CUDA_VISIBLE_DEVICES=0 python main.py --input_path images/input2.png --output_dir output --num_iter 15000 --show_every 1000 --drop_tau 0.1  

Citation

If you find our work useful in your research or publication, please cite it:

@Article{liang2022selfsupervised,
  author  = {Liang, Jinxiu and Xu, Yong and Quan, Yuhui and Shi, Boxin and Ji, Hui},
  title   = {Self-Supervised Low-Light Image Enhancement Using Discrepant Untrained Network Priors},
  journal = {IEEE Transactions on Circuits and Systems for Video Technology},
  year    = {2022},
  pages   = {Early Access},
  issn    = {1558-2205},
  doi     = {10.1109/TCSVT.2022.3181781},
}

Further comments

The code is heavily borrowed from DoubleDIP.

The code is provided as-is for academic use only and without any guarantees. Please contact the author to report any bugs.