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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 851–875 of 1459 papers

TitleStatusHype
DRT: A Lightweight Single Image Deraining Recursive TransformerCode1
Learn from Unpaired Data for Image Restoration: A Variational Bayes ApproachCode1
Image Restoration in Non-Linear Filtering Domain using MDB approach—0
Adaptive Non-linear Filtering Technique for Image Restoration—0
Efficient Progressive High Dynamic Range Image Restoration via Attention and Alignment Network—0
Learning Enriched Features for Fast Image Restoration and Enhancement—0
NAFSSR: Stereo Image Super-Resolution Using NAFNetCode4
Towards Efficient Single Image Dehazing and Desnowing—0
A comparison of different atmospheric turbulence simulation methods for image restoration—0
Heavy Rain Face Image Restoration: Integrating Physical Degradation Model and Facial Component Guided Adversarial Learning—0
MST++: Multi-stage Spectral-wise Transformer for Efficient Spectral ReconstructionCode5
Conditional Injective Flows for Bayesian ImagingCode0
Semi-supervised atmospheric component learning in low-light image problem—0
Residual Swin Transformer Channel Attention Network for Image Demosaicing—0
Simple Baselines for Image RestorationCode4
Evaluating Procedures for Establishing Generative Adversarial Network-based Stochastic Image Models in Medical Imaging—0
RestoreX-AI: A Contrastive Approach towards Guiding Image Restoration via Explainable AI Systems—0
Extremely Low-light Image Enhancement with Scene Text RestorationCode0
Learning to Deblur using Light Field Generated and Real Defocus ImagesCode1
Bayesian Image Super-Resolution with Deep Modeling of Image StatisticsCode1
Coarse to Fine: Image Restoration Boosted by Multi-Scale Low-Rank Tensor CompletionCode0
Unsupervised Deraining: Where Contrastive Learning Meets Self-similarityCode1
Exploring and Evaluating Image Restoration Potential in Dynamic ScenesCode1
Secondary complementary balancing compressive imaging with a free-space balanced amplified photodetector—0
Medium Transmission Map Matters for Learning to Restore Real-World Underwater ImagesCode0
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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