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 1351–1375 of 1459 papers

TitleStatusHype
Pelvic floor MRI segmentation based on semi-supervised deep learning—0
Perceptual Fairness in Image Restoration—0
Perceptual Image Enhancement for Smartphone Real-Time Applications—0
Perceptual Image Restoration with High-Quality Priori and Degradation Learning—0
Performance Analysis of Plug-and-Play ADMM: A Graph Signal Processing Perspective—0
Personalized Generative Low-light Image Denoising and Enhancement—0
Personalized Restoration via Dual-Pivot Tuning—0
PG-DPIR: An efficient plug-and-play method for high-count Poisson-Gaussian inverse problems—0
Physical prior guided cooperative learning framework for joint turbulence degradation estimation and infrared video restoration—0
Physics-Based Generative Adversarial Models for Image Restoration and Beyond—0
Physics-guided Terahertz Computational Imaging—0
PIPAL: a Large-Scale Image Quality Assessment Dataset for Perceptual Image Restoration—0
PIRNet: Privacy-Preserving Image Restoration Network via Wavelet Lifting—0
Plug-and-Play ADMM for Image Restoration: Fixed Point Convergence and Applications—0
PNEN: Pyramid Non-Local Enhanced Networks—0
Unfolded proximal neural networks for robust image Gaussian denoising—0
Poisson Noise Reduction with Higher-order Natural Image Prior Model—0
Posterior sampling via Langevin dynamics based on generative priors—0
Preconditioned Plug-and-Play ADMM with Locally Adjustable Denoiser for Image Restoration—0
Privacy-Preserving Action Recognition using Coded Aperture Videos—0
Probabilistic Prior Driven Attention Mechanism Based on Diffusion Model for Imaging Through Atmospheric Turbulence—0
Procedural Kernel Networks—0
Sequential Hierarchical Learning with Distribution Transformation for Image Super-Resolution—0
Progressive Transfer Learning for Multi-Pass Fundus Image Restoration—0
Proxies for Distortion and Consistency with Applications for Real-World 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