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

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Showing 551–600 of 1459 papers

TitleStatusHype
AutoDIR: Automatic All-in-One Image Restoration with Latent DiffusionCode1
Unifying Image Processing as Visual Prompting Question Answering—0
Frequency-Aware Re-Parameterization for Over-Fitting Based Image Compression—0
Degradation-Aware Self-Attention Based Transformer for Blind Image Super-ResolutionCode1
Deformation-Invariant Neural Network and Its Applications in Distorted Image Restoration and Analysis—0
Leveraging Classic Deconvolution and Feature Extraction in Zero-Shot Image RestorationCode0
A Restoration Network as an Implicit Prior—0
JPEG Information Regularized Deep Image Prior for Denoising—0
Controlling Vision-Language Models for Multi-Task Image RestorationCode2
Survey on Deep Face Restoration: From Non-blind to Blind and BeyondCode1
Uncertainty Quantification via Neural Posterior Principal Components—0
Guided Frequency Loss for Image Restoration—0
On the Posterior Distribution in Denoising: Application to Uncertainty QuantificationCode1
Training Your Image Restoration Network Better with Random Weight Network as Optimization Function—0
Training Your Image Restoration Network Better with Random Weight Network as Optimization Function—0
License Plate Super-Resolution Using Diffusion Models—0
Deshadow-Anything: When Segment Anything Model Meets Zero-shot shadow removal—0
Reconstruct-and-Generate Diffusion Model for Detail-Preserving Image Denoising—0
AOSR-Net: All-in-One Sandstorm Removal Network—0
A Multi-scale Generalized Shrinkage Threshold Network for Image Blind Deblurring in Remote Sensing—0
FAIR: Frequency-aware Image Restoration for Industrial Visual Anomaly DetectionCode1
Learning from History: Task-agnostic Model Contrastive Learning for Image RestorationCode1
HAT: Hybrid Attention Transformer for Image RestorationCode3
Prompt-based Ingredient-Oriented All-in-One Image RestorationCode1
Advanced Underwater Image Restoration in Complex Illumination Conditions—0
SAM-Deblur: Let Segment Anything Boost Image DeblurringCode1
Memory augment is All You Need for image restorationCode1
Holistic Dynamic Frequency Transformer for Image Fusion and Exposure Correction—0
DiffBIR: Towards Blind Image Restoration with Generative Diffusion PriorCode4
Pixel-Aware Stable Diffusion for Realistic Image Super-resolution and Personalized StylizationCode3
MetaWeather: Few-Shot Weather-Degraded Image RestorationCode1
Hierarchical Contrastive Learning for Pattern-Generalizable Image Corruption DetectionCode1
Residual Denoising Diffusion ModelsCode2
MOFA: A Model Simplification Roadmap for Image Restoration on Mobile DevicesCode1
Synergistic Multiscale Detail Refinement via Intrinsic Supervision for Underwater Image EnhancementCode1
Blind Face Restoration for Under-Display Camera via Dictionary Guided Transformer—0
WMFormer++: Nested Transformer for Visible Watermark Removal via Implict Joint Learning—0
Diffusion Models for Image Restoration and Enhancement -- A Comprehensive SurveyCode2
Learning A Coarse-to-Fine Diffusion Transformer for Image RestorationCode1
Under-Display Camera Image Restoration with Scattering EffectCode1
Nest-DGIL: Nesterov-optimized Deep Geometric Incremental Learning for CS Image ReconstructionCode0
Unfolded proximal neural networks for robust image Gaussian denoising—0
All-in-one Multi-degradation Image Restoration Network via Hierarchical Degradation Representation—0
Recurrent Spike-based Image Restoration under General IlluminationCode0
Strip Attention for Image RestorationCode1
Benchmarking Ultra-High-Definition Image Reflection RemovalCode0
Decomposition Ascribed Synergistic Learning for Unified Image Restoration—0
The RoboDepth Challenge: Methods and Advancements Towards Robust Depth EstimationCode2
SuperInpaint: Learning Detail-Enhanced Attentional Implicit Representation for Super-resolutional Image Inpainting—0
Phenotype-preserving metric design for high-content image reconstruction by generative inpaintingCode0
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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