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 71–80 of 1459 papers

TitleStatusHype
An Efficient and Mixed Heterogeneous Model for Image RestorationCode2
Efficient Medical Image Restoration via Reliability Guided Learning in Frequency Domain—0
Beyond Degradation Redundancy: Contrastive Prompt Learning for All-in-One Image RestorationCode1
Enhancing Image Restoration through Learning Context-Rich and Detail-Accurate FeaturesCode0
VibrantLeaves: A principled parametric image generator for training deep restoration modelsCode0
Progressive Transfer Learning for Multi-Pass Fundus Image Restoration—0
PG-DPIR: An efficient plug-and-play method for high-count Poisson-Gaussian inverse problems—0
Computationally iterative methods for salt-and-pepper denoising—0
Beyond Degradation Conditions: All-in-One Image Restoration via HOG TransformersCode1
SIDL: A Real-World Dataset for Restoring Smartphone Images with Dirty Lenses—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