Home

Awesome

ERRNet

The implementation of CVPR 2019 paper "Single Image Reflection Removal Exploiting Misaligned Training Data and Network Enhancements"

News (19/09/2019): Fix the broken link; our pretrained model and collected unaligned dataset are now available at OneDrive

Highlights

<img src="imgs/animation2.gif" height="140px"/> <img src="imgs/animation1.gif" height="140px"/>

<img src="imgs/unaligned1.gif" height="140px"/> <img src="imgs/datacollection_ours.jpg" height="140px"/> <img src="imgs/unaligned2.gif" height="140px"/>

<img src="imgs/unaligned_pixel.gif" height="140px"/> <img src="imgs/unaligned_ours.gif" height="140px"/>

Prerequisites

Quick Start

1. Preparing your training/testing datasets

Training dataset

Testing dataset

Once the data are downloaded, you must organize the dataset according to our code implementation (see the source code of datasets.CEILDataset, e.t.c.)

2. Playing with aligned data

Testing

Training

3. Playing with unaligned data

Citation

If you find our code helpful in your research or work please cite our paper.

 @inproceedings{wei2019single,
   title={Single Image Reflection Removal Exploiting Misaligned Training Data and Network Enhancements},
   author={Wei, Kaixuan and Yang, Jiaolong and Fu, Ying and David, Wipf and Huang, Hua},
   booktitle={IEEE Conference on Computer Vision and Pattern Recognition},
   year={2019},
 }

Contact

If you find any problem, please feel free to contact me (kxwei at princeton.edu kaixuan_wei at bit.edu.cn). A brief self-introduction is required, if you would like to get an in-depth help from me.

Acknowledgments