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Image Reconstruction

Papers

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Showing 1051–1075 of 2143 papers

TitleStatusHype
Human from Blur: Human Pose Tracking from Blurry Images—0
SC-VAE: Sparse Coding-based Variational Autoencoder with Learned ISTACode0
Low-Dose CT Image Reconstruction using Vector Quantized Convolutional Autoencoder with Perceptual Loss—0
SVD-DIP: Overcoming the Overfitting Problem in DIP-based CT ReconstructionCode0
Joint Multi-Echo/Respiratory Motion-Resolved Compressed Sensing Reconstruction of Free-Breathing Non-Cartesian Abdominal MRI—0
AIR-DA: Adversarial Image Reconstruction for Unsupervised Domain Adaptive Object Detection—0
MRI Reconstruction with Side Information using Diffusion Models—0
MindDiffuser: Controlled Image Reconstruction from Human Brain Activity with Semantic and Structural Diffusion—0
SCALES: Boost Binary Neural Network for Image Super-Resolution with Efficient Scalings—0
Parallel Diffusion Model-based Sparse-view Cone-beam Breast CT—0
Image Reconstruction without Explicit Priors—0
Task-based Generation of Optimized Projection Sets using Differentiable Ranking—0
FedMAE: Federated Self-Supervised Learning with One-Block Masked Auto-Encoder—0
Revisiting Image Reconstruction for Semi-supervised Semantic Segmentation—0
SUD^2: Supervision by Denoising Diffusion Models for Image Reconstruction—0
Fast 3D Volumetric Image Reconstruction from 2D MRI Slices by Parallel Processing—0
SMUG: Towards robust MRI reconstruction by smoothed unrollingCode0
Multi PILOT: Learned Feasible Multiple Acquisition Trajectories for Dynamic MRICode0
Improving Masked Autoencoders by Learning Where to Mask—0
Reconstruction of Cardiac Cine MRI Using Motion-Guided Deformable Alignment and Multi-Resolution Fusion—0
Deep Equilibrium Learning of Explicit Regularizers for Imaging Inverse ProblemsCode0
DULDA: Dual-domain Unsupervised Learned Descent Algorithm for PET image reconstruction—0
STPDnet: Spatial-temporal convolutional primal dual network for dynamic PET image reconstruction—0
Diffusion in the Dark: A Diffusion Model for Low-Light Text Recognition—0
Amortized Normalizing Flows for Transcranial Ultrasound with Uncertainty Quantification—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