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 151–175 of 1459 papers

TitleStatusHype
FDG-Diff: Frequency-Domain-Guided Diffusion Framework for Compressed Hazy Image RestorationCode0
Deep Learning-Based Image Recovery and Pose Estimation for Resident Space Objects—0
Proxies for Distortion and Consistency with Applications for Real-World Image Restoration—0
SILO: Solving Inverse Problems with Latent Operators—0
DiffStereo: High-Frequency Aware Diffusion Model for Stereo Image Restoration—0
Knowledge Distillation for Image Restoration : Simultaneous Learning from Degraded and Clean Images—0
Soft Knowledge Distillation with Multi-Dimensional Cross-Net Attention for Image Restoration Models Compression—0
MB-TaylorFormer V2: Improved Multi-branch Linear Transformer Expanded by Taylor Formula for Image RestorationCode2
Color Correction Meets Cross-Spectral Refinement: A Distribution-Aware Diffusion for Underwater Image Restoration—0
Convergent Primal-Dual Plug-and-Play Image Restoration: A General Algorithm and ApplicationsCode0
Underwater Image Restoration Through a Prior Guided Hybrid Sense Approach and Extensive Benchmark AnalysisCode1
ACL: Activating Capability of Linear Attention for Image Restoration—0
JarvisIR: Elevating Autonomous Driving Perception with Intelligent Image Restoration—0
Sea-ing in Low-lightCode0
A Universal Scale-Adaptive Deformable Transformer for Image Restoration across Diverse ArtifactsCode1
Spk2SRImgNet: Super-Resolve Dynamic Scene from Spike Stream via Motion Aligned Collaborative Filtering—0
LP-Diff: Towards Improved Restoration of Real-World Degraded License PlateCode1
Secret Lies in Color: Enhancing AI-Generated Images Detection with Color Distribution Analysis—0
UHD-processer: Unified UHD Image Restoration with Progressive Frequency Learning and Degradation-aware PromptsCode1
VolFormer: Explore More Comprehensive Cube Interaction for Hyperspectral Image Restoration and BeyondCode1
Navigating Image Restoration with VAR's Distribution Alignment PriorCode2
Adaptive Dropout: Unleashing Dropout across Layers for Generalizable Image Super-Resolution—0
Dual Prompting Image Restoration with Diffusion Transformers—0
Adapting Text-to-Image Generation with Feature Difference Instruction for Generic Image Restoration—0
Consistency Posterior Sampling for Diverse Image Synthesis—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