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 1076–1100 of 1459 papers

TitleStatusHype
Face2Face: Label-driven Facial Retouching Restoration—0
Face Generation from Textual Features using Conditionally Trained Inputs to Generative Adversarial Networks—0
FarSight: A Physics-Driven Whole-Body Biometric System at Large Distance and Altitude—0
Fast and Accurate Poisson Denoising with Optimized Nonlinear Diffusion—0
Fast and High-Quality Image Denoising via Malleable Convolutions—0
Fast & Robust Image Interpolation using Gradient Graph Laplacian Regularizer—0
Fast Scalable Image Restoration using Total Variation Priors and Expectation Propagation—0
Feature-Align Network with Knowledge Distillation for Efficient Denoising—0
A Close Look at Few-shot Real Image Super-resolution from the Distortion Relation Perspective—0
Finding the Reflection Point: Unpadding Images to Remove Data Augmentation Artifacts in Large Open Source Image Datasets for Machine Learning—0
Fine Dense Alignment of Image Bursts through Camera Pose and Depth Estimation—0
Fingerprinting Deep Image Restoration Models—0
FINO: Flow-based Joint Image and Noise Model—0
Fractal-IR: A Unified Framework for Efficient and Scalable Image Restoration—0
Fractional Calculus In Image Processing: A Review—0
Fractional differentiation based image processing—0
Frequency-Aware Guidance for Blind Image Restoration via Diffusion Models—0
Frequency-Aware Re-Parameterization for Over-Fitting Based Image Compression—0
Frequency-Guided Posterior Sampling for Diffusion-Based Image Restoration—0
Frequency Regularized Deep Convolutional Dictionary Learning and Application to Blind Denoising—0
From Controlled Scenarios to Real-World: Cross-Domain Degradation Pattern Matching for All-in-One Image Restoration—0
From Posterior Sampling to Meaningful Diversity in Image Restoration—0
FSI: Frequency and Spatial Interactive Learning for Image Restoration in Under-Display Cameras—0
Functional Neural Networks for Parametric Image Restoration Problems—0
Fusion from Decomposition: A Self-Supervised Approach for Image Fusion and Beyond—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