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 51–60 of 1459 papers

TitleStatusHype
Diff-Unfolding: A Model-Based Score Learning Framework for Inverse Problems—0
Behind the Noise: Conformal Quantile Regression Reveals Emergent Representations—0
Generalizable Pancreas Segmentation via a Dual Self-Supervised Learning Framework—0
UnfoldIR: Rethinking Deep Unfolding Network in Illumination Degradation Image Restoration—0
A Preliminary Study for GPT-4o on Image RestorationCode1
SVAD: From Single Image to 3D Avatar via Synthetic Data Generation with Video Diffusion and Data AugmentationCode2
EAM: Enhancing Anything with Diffusion Transformers for Blind Super-Resolution—0
Image Restoration via Multi-domain LearningCode1
Multi-Scale Target-Aware Representation Learning for Fundus Image Enhancement—0
GuideSR: Rethinking Guidance for One-Step High-Fidelity Diffusion-Based Super-Resolution—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