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 801–825 of 1459 papers

TitleStatusHype
Restoring Vision in Adverse Weather Conditions with Patch-Based Denoising Diffusion ModelsCode2
GLEAN: Generative Latent Bank for Image Super-Resolution and BeyondCode5
DnSwin: Toward Real-World Denoising via Continuous Wavelet Sliding-TransformerCode1
Real Image Restoration via Structure-preserving Complementarity Attention—0
REPNP: Plug-and-Play with Deep Reinforcement Learning Prior for Robust Image Restoration—0
Enhancing Image Rescaling using Dual Latent Variables in Invertible Neural NetworkCode0
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
A Survey on Leveraging Pre-trained Generative Adversarial Networks for Image Editing and RestorationCode1
Towards Efficient and Scale-Robust Ultra-High-Definition Image DemoireingCode2
Single Frame Atmospheric Turbulence Mitigation: A Benchmark Study and A New Physics-Inspired Transformer ModelCode1
Deep Semantic Statistics Matching (D2SM) Denoising NetworkCode1
Global-Local Stepwise Generative Network for Ultra High-Resolution Image RestorationCode0
RCRN: Real-world Character Image Restoration Network via Skeleton ExtractionCode0
Structural Prior Guided Generative Adversarial Transformers for Low-Light Image Enhancement—0
Tilt-then-Blur or Blur-then-Tilt? Clarifying the Atmospheric Turbulence Model—0
MSP-Former: Multi-Scale Projection Transformer for Single Image Desnowing—0
Denoising single images by feature ensemble revisited—0
Snow Mask Guided Adaptive Residual Network for Image Snow Removal—0
D2HNet: Joint Denoising and Deblurring with Hierarchical Network for Robust Night Image RestorationCode1
DRL-ISP: Multi-Objective Camera ISP with Deep Reinforcement Learning—0
Degradation-Guided Meta-Restoration Network for Blind Super-Resolution—0
Variational Deep Image RestorationCode1
Training Patch Analysis and Mining Skills for Image Restoration Deep Neural Networks—0
Mockingbird at the SIGTYP 2022 Shared Task: Two Types of Models forthe Prediction of Cognate Reflexes—0
Show:102550
← PrevPage 33 of 59Next →
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