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 826–850 of 1459 papers

TitleStatusHype
The SIGTYP 2022 Shared Task on the Prediction of Cognate ReflexesCode0
NTIRE 2022 Challenge on Perceptual Image Quality Assessment—0
Self-supervised deep image restoration via adaptive stochastic gradient Langevin dynamicsCode1
Masked Frequency Modeling for Self-Supervised Visual Pre-TrainingCode1
Annular Computational Imaging: Capture Clear Panoramic Images through Simple LensCode1
Hypernetwork-Based Adaptive Image RestorationCode1
Toward Real-world Single Image Deraining: A New Benchmark and BeyondCode1
Robust Deep Ensemble Method for Real-world Image DenoisingCode0
Patch-based image Super Resolution using generalized Gaussian mixture model—0
Real-World Image Super-Resolution by Exclusionary Dual-LearningCode1
Priors in Deep Image Restoration and Enhancement: A SurveyCode1
Compound Multi-branch Feature Fusion for Real Image RestorationCode1
NTIRE 2022 Challenge on High Dynamic Range Imaging: Methods and Results—0
Degradation-Aware Unfolding Half-Shuffle Transformer for Spectral Compressive Imaging—0
A theoretical framework for self-supervised MR image reconstruction using sub-sampling via variable density Noisier2NoiseCode1
A Survey on Hyperspectral Image Restoration: From the View of Low-Rank Tensor Approximation—0
Speckle Image Restoration without Clean Data—0
MM-RealSR: Metric Learning based Interactive Modulation for Real-World Super-ResolutionCode1
Semi-Cycled Generative Adversarial Networks for Real-World Face Super-ResolutionCode1
GenISP: Neural ISP for Low-Light Machine CognitionCode1
Physics-guided Terahertz Computational Imaging—0
PnP-ReG: Learned Regularizing Gradient for Plug-and-Play Gradient Descent—0
Deep Generalized Unfolding Networks for Image RestorationCode1
Conformer and Blind Noisy Students for Improved Image Quality AssessmentCode1
Attentive Fine-Grained Structured Sparsity for Image RestorationCode1
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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