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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 581–590 of 1459 papers

TitleStatusHype
CDI: Blind Image Restoration Fidelity Evaluation based on Consistency with Degraded Image—0
INDIGO+: A Unified INN-Guided Probabilistic Diffusion Algorithm for Blind and Non-Blind Image Restoration—0
Binary Diffusion Probabilistic Model—0
UniUIR: Considering Underwater Image Restoration as An All-in-One Learner—0
UniRestore: Unified Perceptual and Task-Oriented Image Restoration Model Using Diffusion Prior—0
Deep Learning-Based Image Recovery and Pose Estimation for Resident Space Objects—0
FDG-Diff: Frequency-Domain-Guided Diffusion Framework for Compressed Hazy Image RestorationCode0
Proxies for Distortion and Consistency with Applications for Real-World Image Restoration—0
SILO: Solving Inverse Problems with Latent Operators—0
DiffStereo: High-Frequency Aware Diffusion Model for Stereo Image Restoration—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