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 461–470 of 1459 papers

TitleStatusHype
Gyroscope-Assisted Motion Deblurring NetworkCode0
Descanning: From Scanned to the Original Images with a Color Correction Diffusion Model—0
U-shaped Vision Mamba for Single Image DehazingCode2
Analysis of Deep Image Prior and Exploiting Self-Guidance for Image Reconstruction—0
Knowledge-driven deep learning for fast MR imaging: undersampled MR image reconstruction from supervised to un-supervised learning—0
Rethinking RGB Color Representation for Image Restoration Models—0
Key-Graph Transformer for Image Restoration—0
LIR: A Lightweight Baseline for Image RestorationCode1
Plug-and-Play image restoration with Stochastic deNOising REgularizationCode1
Diffusion Model Compression for Image-to-Image Translation—0
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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