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Image Reconstruction

Papers

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Showing 1501–1550 of 2143 papers

TitleStatusHype
Solving Inverse Problems With Deep Neural Networks -- Robustness Included?Code1
Augmented Equivariant Attention Networks for Microscopy Image Reconstruction—0
Deep learning for biomedical photoacoustic imaging: A review—0
CaCL: Class-aware Codebook Learning for Weakly Supervised Segmentation on Diffuse Image PatternsCode0
Two-layer clustering-based sparsifying transform learning for low-dose CT reconstruction—0
Adversarial Robust Training of Deep Learning MRI Reconstruction ModelsCode1
Deep Autofocus for Synthetic Aperture Sonar—0
Deep Probabilistic Imaging: Uncertainty Quantification and Multi-modal Solution Characterization for Computational ImagingCode1
Fourth-Order Nonlocal Tensor Decomposition Model for Spectral Computed Tomography—0
Improved Supervised Training of Physics-Guided Deep Learning Image Reconstruction with Multi-Masking—0
D-VDAMP: Denoising-based Approximate Message Passing for Compressive MRICode0
SUREMap: Predicting Uncertainty in CNN-based Image Reconstruction Using Stein's Unbiased Risk EstimateCode0
Face Hallucination via Split-Attention in Split-Attention NetworkCode1
Neural Star Domain as Primitive Representation—0
Recurrent neural network-based volumetric fluorescence microscopy—0
Region-specific Dictionary Learning-based Low-dose Thoracic CT Reconstruction—0
ENSURE: A General Approach for Unsupervised Training of Deep Image Reconstruction Algorithms—0
SPECT Imaging Reconstruction Method Based on Deep Convolutional Neural Network—0
Variational Capsule Encoder—0
XPDNet for MRI Reconstruction: an application to the 2020 fastMRI challengeCode1
When Wireless Communications Meet Computer Vision in Beyond 5G—0
Multi-layer Residual Sparsifying Transform (MARS) Model for Low-dose CT Image Reconstruction—0
CSTNet: A Dual-Branch Convolutional Network for Imaging of Reactive Flows using Chemical Species Tomography—0
Unified Supervised-Unsupervised (SUPER) Learning for X-ray CT Image Reconstruction—0
Physics-based Reconstruction Methods for Magnetic Resonance ImagingCode1
Improving spatial domain based image formation through compressed sensing—0
Sampling possible reconstructions of undersampled acquisitions in MR imagingCode0
S3K: Self-Supervised Semantic Keypoints for Robotic Manipulation via Multi-View Consistency—0
Deep Image Reconstruction using Unregistered Measurements without Groundtruth—0
Deep Artifact-Free Residual Network for Single Image Super-Resolution—0
Complex Convolutional Neural Networks for Ultrafast Ultrasound Image Reconstruction from In-Phase/Quadrature Signal—0
Iterative regularization algorithms for image denoising with the TV-Stokes model—0
Remote sensing image fusion based on Bayesian GAN—0
Back to Event Basics: Self-Supervised Learning of Image Reconstruction for Event Cameras via Photometric Constancy—0
Deep Learning in Photoacoustic Tomography: Current approaches and future directionsCode1
CSI2Image: Image Reconstruction from Channel State Information Using Generative Adversarial Networks—0
Efficient Folded Attention for 3D Medical Image Reconstruction and Segmentation—0
A Residual Solver and Its Unfolding Neural Network for Total Variation Regularized Models—0
Adversarial attacks on deep learning models for fatty liver disease classification by modification of ultrasound image reconstruction method—0
CNN-Based Ultrasound Image Reconstruction for Ultrafast Displacement Tracking—0
Privacy Leakage of SIFT Features via Deep Generative Model based Image ReconstructionCode0
When Image Decomposition Meets Deep Learning: A Novel Infrared and Visible Image Fusion Method—0
Data and Image Prior Integration for Image Reconstruction Using Consensus Equilibrium—0
Image Reconstruction of Static and Dynamic Scenes through Anisoplanatic Turbulence—0
Unsupervised MRI Reconstruction with Generative Adversarial NetworksCode1
Deep Learning based Spectral CT Imaging—0
CNN-Based Image Reconstruction Method for Ultrafast Ultrasound ImagingCode1
Probabilistic Deep Learning for Instance Segmentation—0
Vulnerability of Face Recognition Systems Against Composite Face Reconstruction Attack—0
Uncertainty Analysis in SPECT Reconstruction based on Probabilistic Programming—0
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All datasetsImageNetUltra-High Resolution Image Reconstruction BenchmarkEdge-to-HandbagsEdge-to-ShoesAudio SetImageNet 256x256Edge-to-ClothesSpike-X4K

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Taming-VQGAN (16x16)FID3.64—Unverified
2VQGAN-LC (16x16)FID2.62—Unverified
3MaskGIT-VQGAN (16x16)FID2.28—Unverified
4RQ-VAE (8x8x16)FID1.83—Unverified
5TiTok-S-128FID1.71—Unverified
6MaskBit (16x16)FID1.66—Unverified
7ViT-VQGAN (16x16)FID1.28—Unverified
8Open-Magvit2 (16x16)FID1.17—Unverified
9Mo-VQGAN (16x16x4)FID1.12—Unverified
10IBQ (16x16)FID1—Unverified
#ModelMetricClaimedVerifiedStatus
1VAR (16x16)rFID9.85—Unverified
2VQGAN (16x16)rFID5.95—Unverified
3LlamaGen (16x16)rFID5.59—Unverified
4Open-Magvit2 (16x16)rFID4.18—Unverified
5MGVQ (16x16x4)rFID1.59—Unverified
6SD-VAE (16x16)rFID1.07—Unverified
#ModelMetricClaimedVerifiedStatus
1pix2pixFID96.31—Unverified
2bFTFID74.9—Unverified
3Xian et al._FID60.85—Unverified
4PI-RECFID0.07—Unverified
#ModelMetricClaimedVerifiedStatus
1pix2pixFID197.49—Unverified
2bFTFID121.2—Unverified
3Xian et al._FID44.76—Unverified
4PI-RECFID0.02—Unverified
#ModelMetricClaimedVerifiedStatus
1Ours (STFT: magnitude, L1l=1) W-ReplicateSSIM0.88—Unverified
2Ours (STFT: magnitude, L1l=1) WS-ReplicateSSIM0.86—Unverified
#ModelMetricClaimedVerifiedStatus
1AugVAE-SLFID3.28—Unverified
2AugVAE-MLFID1.04—Unverified
#ModelMetricClaimedVerifiedStatus
1bFTFID58.4—Unverified
#ModelMetricClaimedVerifiedStatus
1SwinSFAverage PSNR39.61—Unverified