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 10911100 of 1459 papers

TitleStatusHype
Feature-Align Network with Knowledge Distillation for Efficient Denoising0
Accelerating Large Kernel Convolutions with Nested Winograd Transformation.pdf0
Deep Unrolled Network for Video Super-Resolution0
A GAN-Based Input-Size Flexibility Model for Single Image Dehazing0
Plug-and-Play gradient-based denoisers applied to CT image enhancementCode0
Learning local regularization for variational image restoration0
Learning to Enhance Visual Quality via Hyperspectral Domain Mapping0
Editorial: Introduction to the Issue on Deep Learning for Image/Video Restoration and Compression0
Deep Iteration Assisted by Multi-level Obey-pixel Network Discriminator (DIAMOND) for Medical Image Recovery0
Image Restoration by Deep Projected GSURE0
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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