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 1126–1150 of 1459 papers

TitleStatusHype
Blind Motion Deblurring through SinGAN Architecture—0
DeepCFL: Deep Contextual Features Learning from a Single Image—0
Data--driven Image Restoration with Option--driven Learning for Big and Small Astronomical Image Datasets—0
Transform Domain Pyramidal Dilated Convolution Networks For Restoration of Under Display Camera ImagesCode0
Blind Image Restoration with Flow Based Priors—0
Convolutional Nonlinear Dictionary with Cascaded Structure Filter Banks—0
Self-Organized Operational Neural Networks for Severe Image Restoration Problems—0
PNEN: Pyramid Non-Local Enhanced Networks—0
Blur-Attention: A boosting mechanism for non-uniform blurred image restoration—0
LIRA: Lifelong Image Restoration from Unknown Blended Distortions—0
UDC 2020 Challenge on Image Restoration of Under-Display Camera: Methods and Results—0
Unsupervised Image Restoration Using Partially Linear DenoisersCode0
Epigraphical Relaxation for Minimizing Layered Mixed Norms—0
Depth image denoising using nuclear norm and learning graph model—0
Stacking Networks Dynamically for Image Restoration Based on the Plug-and-Play Framework—0
Wavelet-Based Dual-Branch Network for Image Demoiréing—0
A regularized deep matrix factorized model of matrix completion for image restorationCode0
PIPAL: a Large-Scale Image Quality Assessment Dataset for Perceptual Image Restoration—0
Learning Disentangled Feature Representation for Hybrid-distorted Image Restoration—0
Sequential Hierarchical Learning with Distribution Transformation for Image Super-Resolution—0
Blur Invariant Kernel-Adaptive Network for Single Image Blind deblurring—0
A deep primal-dual proximal network for image restoration—0
Low-light Image Restoration with Short- and Long-exposure Raw Pairs—0
SAR Image Despeckling by Deep Neural Networks: from a pre-trained model to an end-to-end training strategyCode0
Concatenated Attention Neural Network for Image Restoration—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