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 621–630 of 1459 papers

TitleStatusHype
Bridge the Gap between SNN and ANN for Image Restoration—0
Diff-Unfolding: A Model-Based Score Learning Framework for Inverse Problems—0
Why Are Deep Representations Good Perceptual Quality Features?—0
DiffStereo: High-Frequency Aware Diffusion Model for Stereo Image Restoration—0
Diff-Restorer: Unleashing Visual Prompts for Diffusion-based Universal Image Restoration—0
A Benchmark for Sparse Coding: When Group Sparsity Meets Rank Minimization—0
AgileIR: Memory-Efficient Group Shifted Windows Attention for Agile Image Restoration—0
Bregman Iteration for Correspondence Problems: A Study of Optical Flow—0
DiffGAR: Model-Agnostic Restoration from Generative Artifacts Using Image-to-Image Diffusion Models—0
DiffBody: Human Body Restoration by Imagining with Generative Diffusion Prior—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