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 1351–1360 of 1459 papers

TitleStatusHype
Pelvic floor MRI segmentation based on semi-supervised deep learning—0
Perceptual Fairness in Image Restoration—0
Perceptual Image Enhancement for Smartphone Real-Time Applications—0
Perceptual Image Restoration with High-Quality Priori and Degradation Learning—0
Performance Analysis of Plug-and-Play ADMM: A Graph Signal Processing Perspective—0
Personalized Generative Low-light Image Denoising and Enhancement—0
Personalized Restoration via Dual-Pivot Tuning—0
PG-DPIR: An efficient plug-and-play method for high-count Poisson-Gaussian inverse problems—0
Physical prior guided cooperative learning framework for joint turbulence degradation estimation and infrared video restoration—0
Physics-Based Generative Adversarial Models for Image Restoration and Beyond—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