Yiguo Jiang, Xuhang Chen , Chi-Man Pun📮 , Shuqiang Wang, Wei Feng (📮 Corresponding Author)
University of Macau, SIAT CAS, Huizhou University, Tianjin University
In The Visual Computer
git clone https://github.com/Jiang-maomao/flare-removal.git
cd flare-removal
To train a model with your own data/model, you can edit the config/config.py
and run the following codes.
For single GPU training:
python train.py
For multiple GPUs training:
accelerate config
accelerate launch train.py
If you have difficulties on the usage of accelerate, please refer to Accelerate.
You can use the deflare.ipynb
You can run the evaluate.py
This work was supported in part by the Science and Technology Development Fund, Macau SAR, under Grants 0141/2023/RIA2 and 0193/2023/RIA3.
If you find our work helpful for your research, please cite:
Jiang, Y., Chen, X., Pun, CM. et al. MFDNet: Multi-Frequency Deflare Network for efficient nighttime flare removal. Vis Comput (2024). https://doi.org/10.1007/s00371-024-03540-x