FIRM: Flexible Interactive Reflection reMoval

Dataset and Code for AAAI'25 paper.

Installation

This implementation based on BasicSR which is a open source toolbox for image/video restoration tasks and HINet

python 3.9.5
pytorch 1.11.0
cuda 11.3

git clone https://github.com/megvii-research/NAFNet
cd NAFNet
pip install -r requirements.txt
python setup.py develop --no_cuda_ext

Train

CUDA_VISIBLE_DEVICES=0 python basicsr/train.py -opt options/train/REDS/NAFNet-width64.yml

Datasets

Please download the datasets with contrastive masks from OneDrive

Citations

If our work helps your research or work, please consider citing FIRM.

@inproceedings{chen2025firm,
  title={FIRM: Flexible Interactive Reflection ReMoval},
  author={Chen, Xiao and Jiang, Xudong and Tao, Yunkang and Lei, Zhen and Li, Qing and Lei, Chenyang and Zhang, Zhaoxiang},
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
  volume={39},
  number={2},
  pages={2230--2238},
  year={2025}
}