The shown images are provided by the datasets from IBCLN, ERRNet, SIR2 and the Internet images.
The code and pretrained model for our paper: Location-aware Single Image Reflection Removal [Arxiv Preprint]
Our code has been tested under the following platform and environment:
- Ubuntu. CPU or NVIDIA GPU + CUDA, CuDNN
- Python 3.7.3, Pytorch 1.2.0
- Requirements: numpy, tqdm, Pillow, dominate, scikit-image
- Clone or Download this repo
$ cd Location-aware-SIRR$ mkdir model- Download the pretrained model here
- Move the downloaded model(
model.pth) to./modelfolder
- The example test images are provided in
./test_images/blendfolder - If you have ground truth blackground images, put them into
./test_images/transmissionfolder ( Note that the same pair of images need to be named the same ). - Run
python3 inference.py - The inference results are in the
./resultsfolder
If you find our work helpful to your research, please cite our paper.
@article{dong2020location,
author = {Zheng Dong and Ke Xu and Yin Yang and Hujun Bao and Weiwei Xu and Rynson W.H. Lau},
title = {Location-aware Single Image Reflection Removal},
journal={ArXiv},
volume={abs/2012.07131},
year = {2020}
}
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent