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 1001–1025 of 1459 papers

TitleStatusHype
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
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
Coarse to Fine: Image Restoration Boosted by Multi-Scale Low-Rank Tensor CompletionCode0
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
Unpaired Deep Image Dehazing Using Contrastive Disentanglement Learning—0
TAPE: Task-Agnostic Prior Embedding for Image Restoration—0
HDNet: High-resolution Dual-domain Learning for Spectral Compressive Imaging—0
Alternative design of DeepPDNet in the context of image restoration—0
Revisiting L1 Loss in Super-Resolution: A Probabilistic View and Beyond—0
Tensor Wiener Filter—0
RestoreDet: Degradation Equivariant Representation for Object Detection in Low Resolution Images—0
FaceQgen: Semi-Supervised Deep Learning for Face Image Quality AssessmentCode0
Fast and High-Quality Image Denoising via Malleable Convolutions—0
KNN Local Attention for Image Restoration—0
GIQE: Generic Image Quality Enhancement via Nth Order Iterative Degradation—0
Image Restoration using Feature-guidance—0
A Trained Regularization Approach Based on Born Iterative Method for Electromagnetic Imaging—0
On Asymptotic Linear Convergence of Projected Gradient Descent for Constrained Least Squares—0
SiamTrans: Zero-Shot Multi-Frame Image Restoration with Pre-Trained Siamese Transformers—0
Procedural Kernel Networks—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