The paper and supplementatry material can be found from here.
- Python 3.5+
- PyTorch 0.4.0+
# Prepare the training data
Please use the provided matlab code (https://github.com/q-zh/absorption/tree/main/matlab).
# Download the VGG model
VGG-16 from http://cs.stanford.edu/people/jcjohns/fast-neural-style/models/vgg16.t7
# Run for training
python main.py
Please find pre-traind model here with code: cvpr.
# Prepare the test set
The data folder should include the reflection-contaminated images
# Run for test
python test.py
If you find our code is useful, please cite our paper. If you have any problem of implementation or running the code, please contact us: csqianzheng@gmail.com.
@inproceedings{CVPR2021_zheng_single,
title={Single Image Reflection Removal with Absorption Effect},
author={Zheng, Qian and Shi, Boxin and Chen, Jinnan and Jiang, Xudong and Duan, Ling-Yu and Kot, Alex C},
booktitle={Proceedings of Computer Vision and Pattern Recognition},
year={2021}
}