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 12311240 of 1459 papers

TitleStatusHype
Enhancement of Underwater Images with Statistical Model of Background Light and Optimization of Transmission Map0
Training Image Estimators without Image Ground-TruthCode0
Degrees of Freedom Analysis of Unrolled Neural Networks0
Heavy Rain Image Restoration: Integrating Physics Model and Conditional Adversarial LearningCode0
PMS-Net: Robust Haze Removal Based on Patch Map for Single ImagesCode0
Segmentation-Aware Image Denoising without Knowing True SegmentationCode0
Rethinking Atmospheric Turbulence Mitigation0
Maximum a Posteriori on a Submanifold: a General Image Restoration Method with GAN0
Multi-level Encoder-Decoder Architectures for Image Restoration0
Understanding Opportunities for Efficiency in Single-image Super Resolution Networks0
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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