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 811–820 of 1459 papers

TitleStatusHype
DiffBody: Human Body Restoration by Imagining with Generative Diffusion Prior—0
DiffGAR: Model-Agnostic Restoration from Generative Artifacts Using Image-to-Image Diffusion Models—0
Diff-Restorer: Unleashing Visual Prompts for Diffusion-based Universal Image Restoration—0
DiffStereo: High-Frequency Aware Diffusion Model for Stereo Image Restoration—0
Diff-Unfolding: A Model-Based Score Learning Framework for Inverse Problems—0
Diffusion Image Prior—0
Diffusion Methods for Classification with Pairwise Relationships—0
Diffusion Model-based FOD Restoration from High Distortion in dMRI—0
Dilated Strip Attention Network for Image Restoration—0
DILIE: Deep Internal Learning for Image Enhancement—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