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Physical Model Guided ID (ICME'2020)

Physical Model Guided Deep Image Deraining (ICME'2020) 
@inproceedings{zhu2020physical,
  title={Physical model guided deep image deraining},
  author={Zhu, Honghe and Wang, Cong and Zhang, Yajie and Su, Zhixun and Zhao, Guohui},
  booktitle={2020 IEEE International Conference on Multimedia and Expo (ICME)},
  pages={1--6},
  year={2020},
  organization={IEEE}
}

physical_model_guided


Quantitative Result

The metrics are PSNR/SSIM. Both are evaluated on RGB channels.

NOTE:

  • Due to limited computation resource:
    • batch size is reduced from 32 to 24
    • For Rain1200 and Rain1400, training epochs is reduced from 2000 to 200
Method Rain200L Rain200H Rain800 Rain1200 Rain1400
pmg_c64d5s3 37.84/0.983 28.79/0.897 27.37/0.859 33.12/0.922 31.38/0.919

Pretrained models can be downloaded from here


Network Complexity

Input shape Flops Params
(3, 256, 256) 98.38GFlops 2.77M