Awesome
bdn-refremv
Deep Bidirectional Estimation for Single Image Reflection Removal. This package is the implementation of the paper:
<small>Seeing Deeply and Bidirectionally: A Deep Learning Approach for Single Image Reflection Removal
Jie Yang*, Dong Gong*, Lingqiao Liu, Qinfeng Shi.
In European Conference on Computer Vision (ECCV), 2018. (* Equal contribution)
</small>
Requirements
- Python packages
pytorch>=0.4.0 numpy pillow
- An NVIDIA GPU and CUDA 9.0 or higher
Conda environment
A minimal conda environment for running the test.sh is provided.
conda env create -f env.yml
Usage
-
Download our pretrained model here. Unpack the archive into
model
folder. -
Put test images into
samples
folder, and run scriptbash test.sh
.
Examples and Real-world Testing Images
Two examples (on real-world images taken by a mobile phone) are shown in the following: from left to right: I (observed image with reflection), B (recovered reflection-free image) and R (the intermediate reflection image). Please see details and examples in our paper.
More real-world reflection images can be found in /samples
for testing.
Datasets
The synthetic datasets used for training and testing in our paper:
Citation
If you use this code for your research, please cite our paper:
@inproceedings{eccv18refrmv,
title={Seeing deeply and bidirectionally: a deep learning approach for single image reflection removal},
author={Yang, Jie and Gong, Dong and Liu, Lingqiao and Shi, Qinfeng},
booktitle={Proceedings of the European Conference on Computer Vision (ECCV)},
pages={654--669},
year={2018}
}