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 1161–1170 of 1459 papers

TitleStatusHype
Lossless Compression of Mosaic Images with Convolutional Neural Network Prediction—0
Text Extraction and Restoration of Old Handwritten Documents—0
Reducing the Representation Error of GAN Image Priors Using the Deep Decoder—0
Total Deep Variation for Linear Inverse ProblemsCode1
Neural Architecture Search for Deep Image PriorCode0
Scale-wise Convolution for Image RestorationCode1
Image Restoration using Plug-and-Play CNN MAP DenoisersCode0
PixelRL: Fully Convolutional Network with Reinforcement Learning for Image ProcessingCode0
Interactive Multi-Dimension Modulation with Dynamic Controllable Residual Learning for Image RestorationCode0
DCIL: Deep Contextual Internal Learning for Image Restoration and Image Retargeting—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