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 351–375 of 1459 papers

TitleStatusHype
ConStyle v2: A Strong Prompter for All-in-One Image RestorationCode1
Denoising as Adaptation: Noise-Space Domain Adaptation for Image RestorationCode2
Revitalizing Convolutional Network for Image RestorationCode2
DaLPSR: Leverage Degradation-Aligned Language Prompt for Real-World Image Super-ResolutionCode1
Diffusion Model-based FOD Restoration from High Distortion in dMRI—0
Ultra-High-Definition Image Restoration: New Benchmarks and A Dual Interaction Prior-Driven SolutionCode1
Restorer: Removing Multi-Degradation with All-Axis Attention and Prompt GuidanceCode0
Diffusion-Based Adaptation for Classification of Unknown Degraded ImagesCode0
DSL-FIQA: Assessing Facial Image Quality via Dual-Set Degradation Learning and Landmark-Guided TransformerCode2
3D CBCT Challenge 2024: Improved Cone Beam CT Reconstruction using SwinIR-Based Sinogram and Image Enhancement—0
DemosaicFormer: Coarse-to-Fine Demosaicing Network for HybridEVS CameraCode1
LayeredDoc: Domain Adaptive Document Restoration with a Layer Separation ApproachCode1
One-Step Effective Diffusion Network for Real-World Image Super-ResolutionCode4
DDR: Exploiting Deep Degradation Response as Flexible Image DescriptorCode0
Unleashing the Denoising Capability of Diffusion Prior for Solving Inverse ProblemsCode1
Beware of Aliases -- Signal Preservation is Crucial for Robust Image Restoration—0
Optimal Eye Surgeon: Finding Image Priors through Sparse Generators at InitializationCode0
Diffusion-based image inpainting with internal learningCode0
Correlation Matching Transformation Transformers for UHD Image RestorationCode2
All-In-One Medical Image Restoration via Task-Adaptive RoutingCode2
Sharing Key Semantics in Transformer Makes Efficient Image RestorationCode0
Blind Image Restoration via Fast Diffusion InversionCode3
Fast Samplers for Inverse Problems in Iterative Refinement ModelsCode0
Looks Too Good To Be True: An Information-Theoretic Analysis of Hallucinations in Generative Restoration Models—0
Efficient Degradation-aware Any Image Restoration—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