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Learning Rain Location Prior for Nighttime Deraining

Learning Rain Location Prior for Nighttime Deraining
Fan Zhang, Shaodi You, Yu Li, Ying Fu
ICCV 2023

framework

This repository contains the official implementation and experimental data of the ICCV2023 paper "Learning Rain Location Prior for Nighttime Deraining", by Fan Zhang, Shaodi You, Yu Li, Ying Fu.

Paper | Supp | Data

Update

Dataset

example

The experimental data used in the paper is now publicly available at Kaggle. It is based on GTAV-NightRain dataset and increase the difficulty by enlarging the rain density.

In this new version, we collected 5000 rainy images paired with 500 clean images for the training set, and 500/100 for the test set. Each clean image corresponds to 10/5 rainy images. The image resolution is 1920x1080.

Note

Please note that this is the very data used in the experiments.

However, after checking carefully, we find that there exist a few scenes with misalignments due to operation mistakes during collection. We filter out these scenes and there's about 0.5dB improvement in PSNR, which applys to all evaluated methods.

We plan to re-collect and update these misaligned scenes and provide the updated quantitative results later.

Requirements

You can refer to Uformer and MPRNet for detailed dependency list. Necessary list will be updated later.

Training

bash train.sh

You can

Evaluation

bash test.sh

Metrics

To calculate PSNR and SSIM metrics, you can use the Matlab script

evaluate_PSNR_SSIM.m

or the Python version

python evaluate_PSNR_SSIM.py

The results produced by .py script are slightly different from the .m script.

Checkpoints

ModelDMRLPRPIMPSNRSSIMCheckpoint
UNet36.630.9693UNet.pth
UNet37.080.9715UNet_RLP.pth
UNet37.280.9716UNet_RLP_RPIM.pth
Uformer_T37.450.9720Uformer_T.pth
Uformer_T37.950.9733Uformer_T_RLP.pth
Uformer_T38.440.9749Uformer_T_RLP_RPIM.pth

Citation

If you find this repo useful, please give us a star and consider citing our papers:

@inproceedings{zhang2023learning,
  title={Learning Rain Location Prior for Nighttime Deraining},
  author={Zhang, Fan and You, Shaodi and Li, Yu and Fu, Ying},
  booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},
  pages={13148--13157},
  year={2023}
}

@article{zhang2022gtav,
  title={GTAV-NightRain: Photometric Realistic Large-scale Dataset for Night-time Rain Streak Removal},
  author={Zhang, Fan and You, Shaodi and Li, Yu and Fu, Ying},
  journal={arXiv preprint arXiv:2210.04708},
  year={2022}
}

Acknowledgement

The code is re-organized based on Uformer and MPRNet. Thanks for their great works!

License

MIT license.

CC BY-NC-SA 4.0 for data.