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 476–500 of 1459 papers

TitleStatusHype
ATFaceGAN: Single Face Image Restoration and Recognition from Atmospheric Turbulence—0
Content-adaptive Representation Learning for Fast Image Super-resolution—0
Adaptively Sparse Regularization for Blind Image Restoration—0
ACL: Activating Capability of Linear Attention for Image Restoration—0
Generative Adversarial Networks and Perceptual Losses for Video Super-Resolution—0
Estimation and Restoration of Compositional Degradation Using Convolutional Neural Networks—0
ERL-Net: Entangled Representation Learning for Single Image De-Raining—0
Consistent Diffusion: Denoising Diffusion Model with Data-Consistent Training for Image Restoration—0
Equivariant Denoisers for Image Restoration—0
Consistency Posterior Sampling for Diverse Image Synthesis—0
EquiReg: Equivariance Regularized Diffusion for Inverse Problems—0
AllRestorer: All-in-One Transformer for Image Restoration under Composite Degradations—0
Generative Adversarial Network based on Resnet for Conditional Image Restoration—0
Epigraphical Relaxation for Minimizing Layered Mixed Norms—0
Conformal and Low-Rank Sparse Representation for Image Restoration—0
Concatenated Attention Neural Network for Image Restoration—0
Estimating Sparse Signals with Smooth Support via Convex Programming and Block Sparsity—0
Enhancing Sample Generation of Diffusion Models using Noise Level Correction—0
ESTISR: Adapting Efficient Scene Text Image Super-resolution for Real-Scenes—0
Evaluating Procedures for Establishing Generative Adversarial Network-based Stochastic Image Models in Medical Imaging—0
Evolutionary Neural Architecture Search for Image Restoration—0
Concept for a CMOS Image Sensor Suited for Analog Image Pre-Processing—0
Content-Aware Depth-Adaptive Image Restoration—0
Adaptive Image Restoration for Video Surveillance: A Real-Time Approach—0
Performance of a GPU- and Time-Efficient Pseudo 3D Network for Magnetic Resonance Image Super-Resolution and Motion Artifact Reduction—0
Show:102550
← PrevPage 20 of 59Next →
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