Grand Challenge

Realistic Single Image Recovering in Adverse Weather

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Outdoor scenes are often affected by fog, haze, rain, and smog. Poor visibility in the atmosphere is due to suspended particles.

This challenge is meant to consolidate research efforts about single image recovering in adverse weather, especially hazy and rainy days. The challenge consists of two tracks: Hazy Image Recovering (HIR) and Rainy Image Recovering (RIR). In both tracks the researchers are required to recover sharp images from give degraded (hazy and rainy) inputs.


The dataset consists of two parts: rainy dataset and hazy dataset. Both these two datasets including training, validation, and test data.

Hazy dataset: We provide 3,000 real-world hazy images collected from traffic surveillance scene, all of which are labeled with object bounding boxes and categories (car, bus, bicycle, motorcycle, and pedestrian), for validation and testing purposes.
[Baidu Yun] Passward: w54h

Rainy dataset: We provide 2,495 real rainy images from high-resolution driving videos. They were captured in diverse real traffic locations and scenes during multiple drives, all of which are labeled with object bounding boxes and categories: car, person, bus, bicycle, and motorcycle.
[Google Drive]


Each team will be asked to register prior to the submission period. Registration is now opened, to register please submit the Registration Form to

Team Name    
School/Organization Name    
Team Members' Name    
Email Address    

Important Dates

  • May 12,  Release of testing data.
  • May 27,  Test image submission deadline.
  • May 27,  Deadline for the accompanying papers for possible publication at ICIP 2019. (optional)
  • July    1,  Announcement of the evaluation results.
  • July    1,  Notification for the acceptance of the accompanying papers. (optional)
  • July  15,  Deadline for the submission of accepted camera-ready paper. (optional)


Dr. Jiaying Liu
Associate Professor, Institute of Computer Science and Technology
Peking University, Beijing, P.R. China
Dr. Wenqi Ren
Assistant Professor, Institute of Information Engineering
Chinese Academy of Sciences, Beijing, P.R. China
Dr. Zhangyang Wang
Assistant Professor, Department of Computer Science & Engineering
Texas A&M University, US