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 12111220 of 1459 papers

TitleStatusHype
JPEG Information Regularized Deep Image Prior for Denoising0
K3DN: Disparity-Aware Kernel Estimation for Dual-Pixel Defocus Deblurring0
Kernel Estimation from Salient Structure for Robust Motion Deblurring0
Key-Graph Transformer for Image Restoration0
KNN Local Attention for Image Restoration0
Knowledge Distillation for Image Restoration : Simultaneous Learning from Degraded and Clean Images0
Knowledge-driven deep learning for fast MR imaging: undersampled MR image reconstruction from supervised to un-supervised learning0
L0TV: A New Method for Image Restoration in the Presence of Impulse Noise0
Latent Graph Attention for Enhanced Spatial Context0
LatentINDIGO: An INN-Guided Latent Diffusion Algorithm for Image Restoration0
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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