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 11–20 of 1459 papers

TitleStatusHype
A Survey on Visual MambaCode4
Photo-Realistic Image Restoration in the Wild with Controlled Vision-Language ModelsCode4
InstructIR: High-Quality Image Restoration Following Human InstructionsCode4
DiffBIR: Towards Blind Image Restoration with Generative Diffusion PriorCode4
Zero-Shot Image Restoration Using Denoising Diffusion Null-Space ModelCode4
NAFSSR: Stereo Image Super-Resolution Using NAFNetCode4
Simple Baselines for Image RestorationCode4
DarkIR: Robust Low-Light Image RestorationCode3
FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image RestorationCode3
TSD-SR: One-Step Diffusion with Target Score Distillation for Real-World Image Super-ResolutionCode3
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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