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 211–220 of 1459 papers

TitleStatusHype
Exploring Real&Synthetic Dataset and Linear Attention in Image Restoration—0
Semantic Segmentation Prior for Diffusion-Based Real-World Super-Resolution—0
FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image RestorationCode3
Phaseformer: Phase-based Attention Mechanism for Underwater Image Restoration and BeyondCode1
Beyond Pixels: Text Enhances Generalization in Real-World Image Restoration—0
Blind Inverse Problem Solving Made Easy by Text-to-Image Latent Diffusion—0
Adaptive Blind All-in-One Image RestorationCode1
Complexity Experts are Task-Discriminative Learners for Any Image Restoration—0
Hierarchical Information Flow for Generalized Efficient Image Restoration—0
TSD-SR: One-Step Diffusion with Target Score Distillation for Real-World Image Super-ResolutionCode3
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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