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 13111320 of 1459 papers

TitleStatusHype
Simultaneous Fidelity and Regularization Learning for Image RestorationCode0
Crafting a Toolchain for Image Restoration by Deep Reinforcement LearningCode0
Supervised Convolutional Sparse Coding0
Adaptive Quantile Sparse Image (AQuaSI) Prior for Inverse Imaging ProblemsCode0
A Cascaded Convolutional Neural Network for Single Image Dehazing0
Nonlocal Low-Rank Tensor Factor Analysis for Image Restoration0
Unveiling the invisible - mathematical methods for restoring and interpreting illuminated manuscriptsCode0
Noise2Noise: Learning Image Restoration without Clean DataCode1
Learning-Based Dequantization For Image Restoration Against Extremely Poor Illumination0
Exploiting the Potential of Standard Convolutional Autoencoders for Image Restoration by Evolutionary SearchCode0
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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