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 1151–1200 of 1459 papers

TitleStatusHype
Structured and Localized Image Restoration—0
Multi-Objective CNN Based Algorithm for SAR Despeckling—0
What's in the Image? Explorable Decoding of Compressed Images—0
The Neural Tangent Link Between CNN Denoisers and Non-Local Filters—0
Distilling Image Dehazing With Heterogeneous Task ImitationCode0
Variational-EM-Based Deep Learning for Noise-Blind Image Deblurring—0
Disparity-Aware Domain Adaptation in Stereo Image Restoration—0
All in One Bad Weather Removal Using Architectural Search—0
Efficient Dynamic Scene Deblurring Using Spatially Variant Deconvolution Network With Optical Flow Guided Training—0
Image Restoration from Parametric Transformations using Generative Models—0
The Power of Triply Complementary Priors for Image Compressive Sensing—0
Hyperspectral Image Restoration via Global Total Variation Regularized Local nonconvex Low-Rank matrix Approximation—0
NTIRE 2020 Challenge on Image Demoireing: Methods and Results—0
Neural Differential Equations for Single Image Super-resolution—0
Unsupervised Lesion Detection via Image Restoration with a Normative Prior—0
Attention Based Real Image RestorationCode0
Virtual SAR: A Synthetic Dataset for Deep Learning based Speckle Noise Reduction Algorithms—0
Distributed Learning and Inference with Compressed Images—0
Moire Image Restoration using Multi Level Hyper Vision NetCode0
Real-world Person Re-Identification via Degradation Invariance Learning—0
Deblurring using Analysis-Synthesis Networks Pair—0
A Set-Theoretic Study of the Relationships of Image Models and Priors for Restoration Problems—0
Blur, Noise, and Compression Robust Generative Adversarial Networks—0
BP-DIP: A Backprojection based Deep Image Prior—0
Image Restoration for Under-Display Camera—0
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