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 511520 of 1459 papers

TitleStatusHype
Dual High-Order Total Variation Model for Underwater Image RestorationCode0
Pathology Image Restoration via Mixture of PromptsCode0
Patch-Ordering as a Regularization for Inverse Problems in Image ProcessingCode0
Path-Restore: Learning Network Path Selection for Image RestorationCode0
On learning optimized reaction diffusion processes for effective image restorationCode0
Chasing Better Deep Image Priors between Over- and Under-parameterizationCode0
DriftRec: Adapting diffusion models to blind JPEG restorationCode0
Optimal Eye Surgeon: Finding Image Priors through Sparse Generators at InitializationCode0
CFSNet: Toward a Controllable Feature Space for Image RestorationCode0
A relaxed proximal gradient descent algorithm for convergent plug-and-play with proximal denoiserCode0
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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