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 1301–1350 of 1459 papers

TitleStatusHype
Multi-Scale Representation Learning for Image Restoration with State-Space Model—0
Multi-Scale Target-Aware Representation Learning for Fundus Image Enhancement—0
Multi-Scale Weighted Nuclear Norm Image Restoration—0
Multi-Shot Imaging: Joint Alignment, Deblurring and Resolution-Enhancement—0
Multispectral Image Restoration by Generalized Opponent Transformation Total Variation—0
Multi-Step Guided Diffusion for Image Restoration on Edge Devices: Toward Lightweight Perception in Embodied AI—0
Multitask Identity-Aware Image Steganography via Minimax Optimization—0
Multi-task Image Restoration Guided By Robust DINO Features—0
Multi-weather Image Restoration via Domain Translation—0
Multi-Weather Image Restoration via Histogram-Based Transformer Feature Enhancement—0
NAADA: A Noise-Aware Attention Denoising Autoencoder for Dental Panoramic Radiographs—0
Near-Field SAR Image Restoration Based On Two Dimensional Spatial-Variant Deconvolution—0
Near-filed SAR Image Restoration with Deep Learning Inverse Technique: A Preliminary Study—0
Near-Infrared Coloring via a Contrast-Preserving Mapping Model—0
Near-lossless _-constrained Image Decompression via Deep Neural Network—0
Neural Differential Equations for Single Image Super-resolution—0
Neural information coding for efficient spike-based image denoising—0
NeuroPump: Simultaneous Geometric and Color Rectification for Underwater Images—0
NFResNet: Multi-scale and U-shaped Networks for Deblurring—0
Noise2Stack: Improving Image Restoration by Learning from Volumetric Data—0
Non-blind Image Restoration Based on Convolutional Neural Network—0
Non-Convex Weighted Lp Nuclear Norm based ADMM Framework for Image Restoration—0
Nonlinear Filter Based Image Denoising Using AMF Approach—0
Nonlocal Low-Rank Tensor Factor Analysis for Image Restoration—0
NTIRE 2020 Challenge on Image Demoireing: Methods and Results—0
NTIRE 2021 Challenge on Perceptual Image Quality Assessment—0
NTIRE 2022 Challenge on High Dynamic Range Imaging: Methods and Results—0
NTIRE 2022 Challenge on Perceptual Image Quality Assessment—0
NTIRE 2023 Quality Assessment of Video Enhancement Challenge—0
NTIRE 2024 Quality Assessment of AI-Generated Content Challenge—0
NTIRE 2024 Restore Any Image Model (RAIM) in the Wild Challenge—0
NTIRE 2025 Challenge on RAW Image Restoration and Super-Resolution—0
NTIRE 2025 challenge on Text to Image Generation Model Quality Assessment—0
NTIRE 2025 the 2nd Restore Any Image Model (RAIM) in the Wild Challenge—0
Object Tracking with Correlation Filters using Selective Single Background Patch—0
OmniSSR: Zero-shot Omnidirectional Image Super-Resolution using Stable Diffusion Model—0
On a Mechanism Framework of Autoencoders—0
On Asymptotic Linear Convergence of Projected Gradient Descent for Constrained Least Squares—0
On Convergent Finite Difference Schemes for Variational - PDE Based Image Processing—0
One-Shot Image Restoration—0
On the Proof of Fixed-Point Convergence for Plug-and-Play ADMM—0
On the unreasonable vulnerability of transformers for image restoration -- and an easy fix—0
Operation-wise Attention Network for Tampering Localization Fusion—0
Optimization-Based Image Restoration under Implementation Constraints in Optical Analog Circuits—0
Osmosis: RGBD Diffusion Prior for Underwater Image Restoration—0
Overcoming False Illusions in Real-World Face Restoration with Multi-Modal Guided Diffusion Model—0
PanAdapter: Two-Stage Fine-Tuning with Spatial-Spectral Priors Injecting for Pansharpening—0
Parallax estimation for push-frame satellite imagery: application to super-resolution and 3D surface modeling from Skysat products—0
Patch-Based Image Restoration using Expectation Propagation—0
Patch-based image Super Resolution using generalized Gaussian mixture 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