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 981–990 of 1459 papers

TitleStatusHype
Degradation-Guided Meta-Restoration Network for Blind Super-Resolution—0
Training Patch Analysis and Mining Skills for Image Restoration Deep Neural Networks—0
Mockingbird at the SIGTYP 2022 Shared Task: Two Types of Models forthe Prediction of Cognate Reflexes—0
The SIGTYP 2022 Shared Task on the Prediction of Cognate ReflexesCode0
NTIRE 2022 Challenge on Perceptual Image Quality Assessment—0
Robust Deep Ensemble Method for Real-world Image DenoisingCode0
Patch-based image Super Resolution using generalized Gaussian mixture model—0
NTIRE 2022 Challenge on High Dynamic Range Imaging: Methods and Results—0
Degradation-Aware Unfolding Half-Shuffle Transformer for Spectral Compressive Imaging—0
A Survey on Hyperspectral Image Restoration: From the View of Low-Rank Tensor Approximation—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