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 951–1000 of 1459 papers

TitleStatusHype
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
Decomposer: Semi-supervised Learning of Image Restoration and Image Decomposition—0
Decomposition Ascribed Synergistic Learning for Unified Image Restoration—0
Decouple to Reconstruct: High Quality UHD Restoration via Active Feature Disentanglement and Reversible Fusion—0
Decoupling Degradation and Content Processing for Adverse Weather Image Restoration—0
Deep Blind Image Inpainting—0
Deep Camera Obscura: An Image Restoration Pipeline for Lensless Pinhole Photography—0
DeepCFL: Deep Contextual Features Learning from a Single Image—0
Deep Convolutional Neural Network for Multi-modal Image Restoration and Fusion—0
Deep Dense Multi-scale Network for Snow Removal Using Semantic and Geometric Priors—0
Deep Generative Models for Bayesian Inference on High-Rate Sensor Data: Applications in Automotive Radar and Medical Imaging—0
Deep Iteration Assisted by Multi-level Obey-pixel Network Discriminator (DIAMOND) for Medical Image Recovery—0
Deep Learning-Based Image Recovery and Pose Estimation for Resident Space Objects—0
Deep Learning CT Image Restoration using System Blur and Noise Models—0
Deep Learning with Inaccurate Training Data for Image Restoration—0
Deep Likelihood Network for Image Restoration with Multiple Degradation Levels—0
Deeply Aggregated Alternating Minimization for Image Restoration—0
Deep Networks for Image Super-Resolution with Sparse Prior—0
Deep priors for satellite image restoration with accurate uncertainties—0
Deep Self-Dissimilarities as Powerful Visual Fingerprints—0
Deep Unrolled Network for Video Super-Resolution—0
Deformation-Invariant Neural Network and Its Applications in Distorted Image Restoration and Analysis—0
Degradation-Aware Unfolding Half-Shuffle Transformer for Spectral Compressive Imaging—0
Degradation-Guided Meta-Restoration Network for Blind Super-Resolution—0
Degrees of Freedom Analysis of Unrolled Neural Networks—0
Rethinking deinterlacing for early interlaced videos—0
Denoising and Covariance Estimation of Single Particle Cryo-EM Images—0
Denoising diffusion models for high-resolution microscopy image restoration—0
Denoising single images by feature ensemble revisited—0
Densely Connected High Order Residual Network for Single Frame Image Super Resolution—0
Depth and Image Restoration From Light Field in a Scattering Medium—0
Depth Estimation and Image Restoration by Deep Learning from Defocused Images—0
Depth image denoising using nuclear norm and learning graph model—0
Descanning: From Scanned to the Original Images with a Color Correction Diffusion Model—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