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EFINet: Restoration for Low-light Images via Enhancement-Fusion Iterative Network

📚 This repo is the official PyTorch implementation of <a href="data/EFINet.pdf" target="_blank" style="text-decoration: none;">EFINet</a>.

<img src=data/EFINet_architecture.png width="85%"/>

Requirements

python 3.7  
torch 1.4.0  
torchvision 0.2.1  
cuda 10.1  
numpy  
opencv

Usage

The results will be saved at data/result.

python lowlight_test.py

The script processes images located in the subfolders of the test_data directory and creates a new result folder within the data directory. The enhanced images will be available in the result folder.

Citation

If you find this work useful for your research, please consider citing our paper

@ARTICLE{liu2022efinet,
  title={EFINet: Restoration for Low-light Images via Enhancement-Fusion Iterative Network}, 
  author={Liu, Chunxiao and Wu, Fanding and Wang, Xun},
  journal={IEEE Transactions on Circuits and Systems for Video Technology}, 
  year={2022},
  volume={32},
  number={12},
  pages={8486-8499},
  doi={10.1109/TCSVT.2022.3195996}}