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 751–775 of 1459 papers

TitleStatusHype
Convergence Analysis of a Proximal Stochastic Denoising Regularization Algorithm—0
Convergent plug-and-play with proximal denoiser and unconstrained regularization parameter—0
Convex Variational Image Restoration with Histogram Priors—0
Convolutional Neural Pyramid for Image Processing—0
Convolutional Nonlinear Dictionary with Cascaded Structure Filter Banks—0
CoT-MISR:Marrying Convolution and Transformer for Multi-Image Super-Resolution—0
Counting Crowds in Bad Weather—0
Coupling Model-Driven and Data-Driven Methods for Remote Sensing Image Restoration and Fusion—0
Covariance Trees for 2D and 3D Processing—0
Cross-Scale Residual Network for Multiple Tasks:Image Super-resolution, Denoising, and Deblocking—0
Cryo-Electron Microscopy Image Analysis Using Multi-Frequency Vector Diffusion Maps—0
CT Super-resolution GAN Constrained by the Identical, Residual, and Cycle Learning Ensemble(GAN-CIRCLE)—0
CU-Mamba: Selective State Space Models with Channel Learning for Image Restoration—0
Cutting-Edge Techniques for Depth Map Super-Resolution—0
DA2Diff: Exploring Degradation-aware Adaptive Diffusion Priors for All-in-One Weather Restoration—0
DarkShot: Lighting Dark Images with Low-Compute and High-Quality—0
DarkVision: A Benchmark for Low-light Image/Video Perception—0
Data augmentation for deep learning based accelerated MRI reconstruction—0
Data--driven Image Restoration with Option--driven Learning for Big and Small Astronomical Image Datasets—0
Data-free Distillation with Degradation-prompt Diffusion for Multi-weather Image Restoration—0
DCIL: Deep Contextual Internal Learning for Image Restoration and Image Retargeting—0
DDS2M: Self-Supervised Denoising Diffusion Spatio-Spectral Model for Hyperspectral Image Restoration—0
Deblurring Processor for Motion-Blurred Faces Based on Generative Adversarial Networks—0
Deblurring Text Images via L0-Regularized Intensity and Gradient Prior—0
Deblurring using Analysis-Synthesis Networks Pair—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