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 1176–1200 of 1459 papers

TitleStatusHype
Blind Image Restoration without Prior Knowledge—0
PSF--NET: A Non-parametric Point Spread Function Model for Ground Based Optical Telescopes—0
Motion Deblurring using Spatiotemporal Phase Aperture Coding—0
H-OWAN: Multi-distorted Image Restoration with Tensor 1x1 Convolution—0
Lossless Compression of Mosaic Images with Convolutional Neural Network Prediction—0
Reducing the Representation Error of GAN Image Priors Using the Deep Decoder—0
Text Extraction and Restoration of Old Handwritten Documents—0
Neural Architecture Search for Deep Image PriorCode0
Image Restoration using Plug-and-Play CNN MAP DenoisersCode0
PixelRL: Fully Convolutional Network with Reinforcement Learning for Image ProcessingCode0
Interactive Multi-Dimension Modulation with Dynamic Controllable Residual Learning for Image RestorationCode0
DCIL: Deep Contextual Internal Learning for Image Restoration and Image Retargeting—0
Multiframe-based Adaptive Despeckling Algorithm for Ultrasound B-mode Imaging with Superior Edge and Texture—0
Training Image Estimators without Image Ground TruthCode0
Microscopy Image Restoration with Deep Wiener-Kolmogorov filtersCode0
HighEr-Resolution Network for Image Demosaicing and EnhancingCode0
0-1 phase transitions in sparse spiked matrix estimation—0
Reversible Adversarial Attack based on Reversible Image Transformation—0
Cross-Scale Residual Network for Multiple Tasks:Image Super-resolution, Denoising, and Deblocking—0
Cooperative Semantic Segmentation and Image Restoration in Adverse Environmental Conditions—0
Multi-defect microscopy image restoration under limited data conditions—0
On the Proof of Fixed-Point Convergence for Plug-and-Play ADMM—0
SUPER Learning: A Supervised-Unsupervised Framework for Low-Dose CT Image Reconstruction—0
Block based refitting in _12 sparse regularisation—0
Image Restoration Using Deep Regulated Convolutional NetworksCode0
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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