Papers › All-in-One Image Restoration for Unknown Corruption
All-in-One Image Restoration for Unknown Corruption
Boyun Li, Xiao Liu, Peng Hu, Zhongqin Wu, Jiancheng Lv, Xi Peng
In this paper, we study a challenging problem in image restoration, namely, how to develop an all-in-one method that could recover images from a variety of unknown corruption types and levels. To this end, we propose an All-in-one Image Restoration Network (AirNet) consisting of two neural modules, named Contrastive-Based Degraded Encoder (CBDE) and Degradation-Guided Restoration Network (DGRN). The major advantages of AirNet are two-fold. First, it is an all-in-one solution which could recover various degraded images in one network. Second, AirNet is free from the prior of the corruption types and levels, which just uses the observed corrupted image to perform inference. These two advantages enable AirNet to enjoy better flexibility and higher economy in real world scenarios wherein the priors on the corruptions are hard to know and the degradation will change with space and time. Extensive experimental results show the proposed method outperforms 17 image restoration baselines on four challenging datasets. The code is available at https://github.com/XLearning-SCU/2022-CVPR-AirNet.
Code
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| 5-Degradation Blind All-in-One Image Restoration | 5-Degradation Blind All-in-One Image Restoration | AirNet | Average PSNR | 25.49 | #7 of 7 | Archive leaderboard | report |
| Blind All-in-One Image Restoration | 3-Degradations | AirNet | Average PSNR | 31.20 | #9 of 9 | Archive leaderboard | report |
| Blind All-in-One Image Restoration | 3-Degradations | AirNet | SSIM | 0.910 | #9 of 9 | Archive leaderboard | report |
| Blind All-in-One Image Restoration | 5-Degradations | AirNet | Average PSNR | 25.49 | #9 of 9 | Archive leaderboard | report |
| Blind All-in-One Image Restoration | 5-Degradations | AirNet | SSIM | 0.846 | #9 of 9 | Archive leaderboard | report |
| Image Restoration | CDD-11 | AirNet | Average PSNR (dB) | 23.75 | #12 of 14 | Archive leaderboard | report |
| Image Restoration | CDD-11 | AirNet | SSIM | 0.8140 | #12 of 14 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
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