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 461470 of 1459 papers

TitleStatusHype
Ambient Diffusion Posterior Sampling: Solving Inverse Problems with Diffusion Models trained on Corrupted DataCode1
PD-GAN: Probabilistic Diverse GAN for Image InpaintingCode1
End-to-End Learning for Joint Image Demosaicing, Denoising and Super-ResolutionCode1
Learning Self-prior for Mesh Denoising using Dual Graph Convolutional NetworksCode1
Compound Multi-branch Feature Fusion for Real Image RestorationCode1
Reconciling Stochastic and Deterministic Strategies for Zero-shot Image Restoration using Diffusion Model in DualCode1
Region-Adaptive Deformable Network for Image Quality AssessmentCode1
Rethinking Image Deraining via Rain Streaks and VaporsCode1
Scientific Image Restoration AnywhereCode1
Taming Diffusion Prior for Image Super-Resolution with Domain Shift SDEsCode1
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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