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

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Showing 261–270 of 1459 papers

TitleStatusHype
Learning Efficient and Effective Trajectories for Differential Equation-based Image RestorationCode2
SITCOM: Step-wise Triple-Consistent Diffusion Sampling for Inverse ProblemsCode0
Overcoming False Illusions in Real-World Face Restoration with Multi-Modal Guided Diffusion Model—0
Diffusion State-Guided Projected Gradient for Inverse ProblemsCode1
PnP-Flow: Plug-and-Play Image Restoration with Flow MatchingCode2
Posterior sampling via Langevin dynamics based on generative priors—0
GLMHA A Guided Low-rank Multi-Head Self-Attention for Efficient Image Restoration and Spectral Reconstruction—0
Posterior-Mean Rectified Flow: Towards Minimum MSE Photo-Realistic Image RestorationCode4
A Survey on Diffusion Models for Inverse Problems—0
UIR-LoRA: Achieving Universal Image Restoration through Multiple Low-Rank AdaptationCode0
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All datasetsCDD-11UHDM.

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1OneRestoreAverage PSNR (dB)28.72—Unverified
2SRUDCAverage PSNR (dB)27.64—Unverified
3RestormerAverage PSNR (dB)26.99—Unverified
4WGWSNetAverage PSNR (dB)26.96—Unverified
5DGUNetAverage PSNR (dB)26.92—Unverified
6OKNetAverage PSNR (dB)26.33—Unverified
7MIRNetAverage PSNR (dB)25.97—Unverified
8PromptIRAverage PSNR (dB)25.9—Unverified
9MPRNetAverage PSNR (dB)25.47—Unverified
10MIRNetv2Average PSNR (dB)25.37—Unverified
#ModelMetricClaimedVerifiedStatus
1ESDNet-LPSNR22.42—Unverified
2ESDNetPSNR22.12—Unverified
#ModelMetricClaimedVerifiedStatus
1730L37—Unverified