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 1026–1050 of 1459 papers

TitleStatusHype
Kernel-aware Burst Blind Super-ResolutionCode0
U2-Former: A Nested U-shaped Transformer for Image Restoration—0
Deep Self-Dissimilarities as Powerful Visual Fingerprints—0
Performance of a GPU- and Time-Efficient Pseudo 3D Network for Magnetic Resonance Image Super-Resolution and Motion Artifact Reduction—0
Learning Discriminative Shrinkage Deep Networks for Image DeconvolutionCode0
A Close Look at Few-shot Real Image Super-resolution from the Distortion Relation Perspective—0
A Novel Framework for Image-to-image Translation and Image Compression—0
An Educated Warm Start For Deep Image Prior-Based Micro CT ReconstructionCode0
A Study on the Efficient Product Search Service for the Damaged Image Information—0
FINO: Flow-based Joint Image and Noise Model—0
ISP-Agnostic Image Reconstruction for Under-Display Cameras—0
Functional Neural Networks for Parametric Image Restoration Problems—0
An Effective Image Restorer: Denoising and Luminance Adjustment for Low-photon-count Imaging—0
Unsupervised PET Reconstruction from a Bayesian Perspective—0
Learning Continuous Face Representation with Explicit Functions—0
Unsupervised Image Fusion Using Deep Image Priors—0
Towards General Deep Leakage in Federated LearningCode0
Identity-guided Face Generation with Multi-modal Contour Conditions—0
Fast Scalable Image Restoration using Total Variation Priors and Expectation Propagation—0
Preconditioned Plug-and-Play ADMM with Locally Adjustable Denoiser for Image Restoration—0
Lottery Image Prior—0
Residual Contrastive Learning: Unsupervised Representation Learning from Residuals—0
Unfolding Taylor's Approximations for Image Restoration—0
Unpaired Deep Image Deraining Using Dual Contrastive Learning—0
Spatially-Adaptive Image Restoration using Distortion-Guided NetworksCode0
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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