Paper | Project Page | Video
Yuekun Dai, Yihang Luo, Shangchen Zhou, Chongyi Li, Chen Change Loy
S-Lab, Nanyang Technological University
- 2022.03.22: Our BracketFlare dataset and pretrained model is uploaded to the Google Drive and Baidu Netdisk now.
- 2022.03.21: Our paper is selected as a highlight (top2.5%) at CVPR 2023.
- 2023.02.28: Our paper Nighttime Smartphone Reflective Flare Removal using Optical Center Symmetry Prior is accepted by the CVPR2023 with 3 top ratings. 🤗
Baidu Netdisk | Google Drive | Number | Description | |
---|---|---|---|---|
BracketFlare | link | link | 440 | We offer 440 normal-exposure and short-exposure nighttime image pairs. Short exposure images can be added to the corresponding normal-exposure image to synthesize the flare-corrupted image. |
├── BracketFlare
├── flare
├── gt
├── test
├── flare
├── gt
├── mask
├── lq
The inference code based on MPRNet is released Now. You can download the pretrained checkpoints on [GoogleDrive | Baidu Netdisk]. Please place it under the experiments
folder and unzip it.
To generate the flare-free images from the test/lq
folder, you can run the test.py
by using:
python test.py --i test/lq/ --o result/ --model_path expirements/net_g_last.pth
To calculate different metrics with our pretrained model, you can run the evaluate.py
by using:
python evaluate.py --input result/deflare/ --gt test/gt --mask test/mask
This project is licensed under S-Lab License 1.0. Redistribution and use of the dataset and code for non-commercial purposes should follow this license. This project is built on BasicSR, the detailed tutorial on training commands and config settings can be found here.
If you find this work useful, please cite:
@inproceedings{dai2023nighttime,
title={Nighttime Smartphone Reflective Flare Removal using Optical Center Symmetry Prior},
author={Dai, Yuekun and Luo, Yihang and Zhou, Shangchen and Li, Chongyi and Loy, Chen Change},
booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
year = {2023}
}
If you have any question (such as asking for the 4K version of our BracketFlare Dataset), please feel free to reach me out at ydai005@e.ntu.edu.sg
.