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 10211030 of 1459 papers

TitleStatusHype
Learning local regularization for variational image restoration0
Learning to Enhance Visual Quality via Hyperspectral Domain Mapping0
Editorial: Introduction to the Issue on Deep Learning for Image/Video Restoration and Compression0
Deep Iteration Assisted by Multi-level Obey-pixel Network Discriminator (DIAMOND) for Medical Image Recovery0
Image Restoration by Deep Projected GSURE0
Multi-Stage Progressive Image RestorationCode1
Parallax estimation for push-frame satellite imagery: application to super-resolution and 3D surface modeling from Skysat products0
Exploiting Raw Images for Real-Scene Super-ResolutionCode1
Non-uniform Blur Kernel Estimation via Adaptive Basis DecompositionCode1
Despeckling Sentinel-1 GRD images by deep learning and application to narrow river segmentationCode0
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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