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

Showing 101125 of 1459 papers

TitleStatusHype
Learning A Sparse Transformer Network for Effective Image DerainingCode2
DiffIR: Efficient Diffusion Model for Image RestorationCode2
KBNet: Kernel Basis Network for Image RestorationCode2
Efficient and Explicit Modelling of Image Hierarchies for Image RestorationCode2
I^2SB: Image-to-Image Schrödinger BridgeCode2
Image Restoration with Mean-Reverting Stochastic Differential EquationsCode2
Efficient Frequency Domain-based Transformers for High-Quality Image DeblurringCode2
A Survey of Deep Face Restoration: Denoise, Super-Resolution, Deblur, Artifact RemovalCode2
Swin2SR: SwinV2 Transformer for Compressed Image Super-Resolution and RestorationCode2
Restoring Vision in Adverse Weather Conditions with Patch-Based Denoising Diffusion ModelsCode2
Unsupervised Night Image Enhancement: When Layer Decomposition Meets Light-Effects SuppressionCode2
DC-ShadowNet: Single-Image Hard and Soft Shadow Removal Using Unsupervised Domain-Classifier Guided NetworkCode2
Towards Efficient and Scale-Robust Ultra-High-Definition Image DemoireingCode2
SUNet: Swin Transformer UNet for Image DenoisingCode2
Deep Constrained Least Squares for Blind Image Super-ResolutionCode2
Denoising Diffusion Restoration ModelsCode2
All-in-One Image Restoration for Unknown CorruptionCode2
Improving Image Restoration by Revisiting Global Information AggregationCode2
GAN Inversion: A SurveyCode2
Mean Deviation Similarity Index: Efficient and Reliable Full-Reference Image Quality EvaluatorCode2
LD-RPS: Zero-Shot Unified Image Restoration via Latent Diffusion Recurrent Posterior SamplingCode1
Visual-Instructed Degradation Diffusion for All-in-One Image RestorationCode1
Unsupervised Imaging Inverse Problems with Diffusion Distribution MatchingCode1
IRBridge: Solving Image Restoration Bridge with Pre-trained Generative Diffusion ModelsCode1
Boosting All-in-One Image Restoration via Self-Improved Privilege LearningCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1OneRestoreAverage PSNR (dB)28.72Unverified
2SRUDCAverage PSNR (dB)27.64Unverified
3RestormerAverage PSNR (dB)26.99Unverified
4WGWSNetAverage PSNR (dB)26.96Unverified
5DGUNetAverage PSNR (dB)26.92Unverified
6OKNetAverage PSNR (dB)26.33Unverified
7MIRNetAverage PSNR (dB)25.97Unverified
8PromptIRAverage PSNR (dB)25.9Unverified
9MPRNetAverage PSNR (dB)25.47Unverified
10MIRNetv2Average PSNR (dB)25.37Unverified
#ModelMetricClaimedVerifiedStatus
1ESDNet-LPSNR22.42Unverified
2ESDNetPSNR22.12Unverified
#ModelMetricClaimedVerifiedStatus
1730L37Unverified