SOTAVerified

Image Restoration

Image Restoration is a family of inverse problems for obtaining a high quality image from a corrupted input image. Corruption may occur due to the image-capture process (e.g., noise, lens blur), post-processing (e.g., JPEG compression), or photography in non-ideal conditions (e.g., haze, motion blur).

Source: Blind Image Restoration without Prior Knowledge

Papers

Showing 321330 of 1459 papers

TitleStatusHype
HPPP: Halpern-type Preconditioned Proximal Point Algorithms and Applications to Image RestorationCode0
Training-Free Large Model Priors for Multiple-in-One Image Restoration0
Restore Anything Model via Efficient Degradation AdaptationCode1
Attention-Guided Low-Rank Tensor CompletionCode1
GRIDS: Grouped Multiple-Degradation Restoration with Image Degradation Similarity0
Haze-Aware Attention Network for Single-Image Dehazing0
MoE-DiffIR: Task-customized Diffusion Priors for Universal Compressed Image Restoration0
In-Loop Filtering via Trained Look-Up Tables0
Restore-RWKV: Efficient and Effective Medical Image Restoration with RWKVCode2
Restoring Images in Adverse Weather Conditions via Histogram TransformerCode3
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1OneRestoreAverage PSNR (dB)28.72Unverified
2SRUDCAverage PSNR (dB)27.64Unverified
3RestormerAverage PSNR (dB)26.99Unverified
4WGWSNetAverage PSNR (dB)26.96Unverified
5DGUNetAverage PSNR (dB)26.92Unverified
6OKNetAverage PSNR (dB)26.33Unverified
7MIRNetAverage PSNR (dB)25.97Unverified
8PromptIRAverage PSNR (dB)25.9Unverified
9MPRNetAverage PSNR (dB)25.47Unverified
10MIRNetv2Average PSNR (dB)25.37Unverified
#ModelMetricClaimedVerifiedStatus
1ESDNet-LPSNR22.42Unverified
2ESDNetPSNR22.12Unverified
#ModelMetricClaimedVerifiedStatus
1730L37Unverified