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 10311040 of 1459 papers

TitleStatusHype
Learning a Non-Blind Deblurring Network for Night Blurry Images0
Learning-Based Dequantization For Image Restoration Against Extremely Poor Illumination0
Learning Continuous Face Representation with Explicit Functions0
Learning Diffusion Texture Priors for Image Restoration0
Learning Discriminative Data Fitting Functions for Blind Image Deblurring0
Learning Disentangled Feature Representation for Hybrid-distorted Image Restoration0
Learning Dynamic Guidance for Depth Image Enhancement0
Learning Enriched Features for Fast Image Restoration and Enhancement0
Learning Frequency-Aware Dynamic Transformers for All-In-One Image Restoration0
Learning from Pseudo Lesion: A Self-supervised Framework for COVID-19 Diagnosis0
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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