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

Showing 10911100 of 1459 papers

TitleStatusHype
Epigraphical Relaxation for Minimizing Layered Mixed Norms0
Depth image denoising using nuclear norm and learning graph model0
Rethinking Image Deraining via Rain Streaks and VaporsCode1
Wavelet-Based Dual-Branch Network for Image Demoiréing0
Stacking Networks Dynamically for Image Restoration Based on the Plug-and-Play Framework0
A regularized deep matrix factorized model of matrix completion for image restorationCode0
PIPAL: a Large-Scale Image Quality Assessment Dataset for Perceptual Image Restoration0
Learning Disentangled Feature Representation for Hybrid-distorted Image Restoration0
Sequential Hierarchical Learning with Distribution Transformation for Image Super-Resolution0
Wavelet-Based Dual-Branch Network for Image DemoireingCode1
Show:102550
← PrevPage 110 of 146Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1OneRestoreAverage PSNR (dB)28.72Unverified
2SRUDCAverage PSNR (dB)27.64Unverified
3RestormerAverage PSNR (dB)26.99Unverified
4WGWSNetAverage PSNR (dB)26.96Unverified
5DGUNetAverage PSNR (dB)26.92Unverified
6OKNetAverage PSNR (dB)26.33Unverified
7MIRNetAverage PSNR (dB)25.97Unverified
8PromptIRAverage PSNR (dB)25.9Unverified
9MPRNetAverage PSNR (dB)25.47Unverified
10MIRNetv2Average PSNR (dB)25.37Unverified
#ModelMetricClaimedVerifiedStatus
1ESDNet-LPSNR22.42Unverified
2ESDNetPSNR22.12Unverified
#ModelMetricClaimedVerifiedStatus
1730L37Unverified