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Image Reconstruction

Papers

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Showing 1001–1050 of 2143 papers

TitleStatusHype
Images from the Mind: BCI image evolution based on Rapid Serial Visual Presentation of polygon primitives—0
Image-Space Gridding for Nonrigid Motion-Corrected MR Image Reconstruction—0
Practical Operator Sketching Framework for Accelerating Iterative Data-Driven Solutions in Inverse Problems—0
3D endoscopic depth estimation using 3D surface-aware constraints—0
Image Translation by Latent Union of Subspaces for Cross-Domain Plaque Detection—0
Image Translation by Latent Union of Subspaces for Cross-Domain Plaque Segmentation—0
Computational Hyperspectral Imaging Based on Dimension-Discriminative Low-Rank Tensor Recovery—0
FixPix: Fixing Bad Pixels using Deep Learning—0
Computational ghost imaging using a field-programmable gate array—0
A Polarization-Aided Transformer for Image Deblurring via Motion Vector Decomposition—0
Finite Hilbert Transform in Weighted L2 Spaces—0
Computational distributed fiber-optic sensing—0
Fingerprint Recognition under Missing Image Pixels Scenario—0
Fidelity Imposed Network Edit (FINE) for Solving Ill-Posed Image Reconstruction—0
A Plug-and-Play Untrained Neural Network for Full Waveform Inversion in Reconstructing Sound Speed Images of Ultrasound Computed Tomography—0
ADMM-Net: A Deep Learning Approach for Compressive Sensing MRI—0
Implicit neural representations for end-to-end PET reconstruction—0
Implicit Neural Representations for Speed-of-Sound Estimation in Ultrasound—0
FG-Depth: Flow-Guided Unsupervised Monocular Depth Estimation—0
Compressive Recovery of Signals Defined on Perturbed Graphs—0
Few-shot Transfer Learning for Holographic Image Reconstruction using a Recurrent Neural Network—0
Few-shot Shape Recognition by Learning Deep Shape-aware Features—0
Compressive radio-interferometric sensing with random beamforming as rank-one signal covariance projections—0
Few-shot Image Generation via Style Adaptation and Content Preservation—0
Compressive Image Recovery Using Recurrent Generative Model—0
FedMAE: Federated Self-Supervised Learning with One-Block Masked Auto-Encoder—0
Federated Low-Rank Tensor Estimation for Multimodal Image Reconstruction—0
Compression, Restoration, Re-sampling, Compressive Sensing: Fast Transforms in Digital Imaging—0
A plug-and-play synthetic data deep learning for undersampled magnetic resonance image reconstruction—0
Accelerating Cardiac MRI Reconstruction with CMRatt: An Attention-Driven Approach—0
FedAutoMRI: Federated Neural Architecture Search for MR Image Reconstruction—0
Compressing deep quaternion neural networks with targeted regularization—0
Feature reconstruction from incomplete tomographic data without detour—0
Feature Extraction Matters More: Universal Deepfake Disruption through Attacking Ensemble Feature Extractors—0
Compressible Latent-Space Invertible Networks for Generative Model-Constrained Image Reconstruction—0
Feature-Driven Super-Resolution for Object Detection—0
Compressed Sensing SAR Imaging with Multilook Processing—0
FCDM: A Physics-Guided Bidirectional Frequency Aware Convolution and Diffusion-Based Model for Sinogram Inpainting—0
Fast X-ray CT image reconstruction using the linearized augmented Lagrangian method with ordered subsets—0
Compressed Sensing Plus Motion (CS+M): A New Perspective for Improving Undersampled MR Image Reconstruction—0
A Picture is Worth a Billion Bits: Real-Time Image Reconstruction from Dense Binary Pixels—0
ADIR: Adaptive Diffusion for Image Reconstruction—0
Fast Sampling generative model for Ultrasound image reconstruction—0
Compressed Sensing for Photoacoustic Computed Tomography Using an Untrained Neural Network—0
Fast PET reconstruction using Multi-scale Fully Convolutional Neural Networks—0
Compressed sensing for longitudinal MRI: An adaptive-weighted approach—0
A Perspective on Deep Imaging—0
Fast Object Classification in Single-pixel Imaging—0
Compressed Sensing, ASBSR-method of image sampling and reconstruction and the problem of digital image acquisition with the lowest possible sampling rate—0
Fast Multi-class Dictionaries Learning with Geometrical Directions in MRI Reconstruction—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