SOTAVerified

3D Reconstruction

3D Reconstruction is the task of creating a 3D model or representation of an object or scene from 2D images or other data sources. The goal of 3D reconstruction is to create a virtual representation of an object or scene that can be used for a variety of purposes, such as visualization, animation, simulation, and analysis. It can be used in fields such as computer vision, robotics, and virtual reality.

Image: Gwak et al

Papers

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Showing 1301–1325 of 2326 papers

TitleStatusHype
HyperLISTA-ABT: An Ultra-light Unfolded Network for Accurate Multi-component Differential Tomographic SAR Inversion—0
3D Reconstruction with Generalizable Neural Fields using Scene Priors—0
PHRIT: Parametric Hand Representation with Implicit Template—0
Unsupervised Multi-Person 3D Human Pose Estimation From 2D Poses Alone—0
Deep learning based workflow for accelerated industrial X-ray Computed Tomography—0
SE(3) Equivariant Convolution and Transformer in Ray Space—0
SE(3) Equivariant Convolution and Transformer in Ray Space—0
SHOWMe: Benchmarking Object-agnostic Hand-Object 3D Reconstruction—0
Improving Neural Indoor Surface Reconstruction with Mask-Guided Adaptive Consistency Constraints—0
Exploiting Multiple Priors for Neural 3D Indoor Reconstruction—0
Semantic and Articulated Pedestrian Sensing Onboard a Moving Vehicle—0
PAg-NeRF: Towards fast and efficient end-to-end panoptic 3D representations for agricultural robotics—0
Cryo-Electron Ptychography: Applications and Potential in Biological Characterisation—0
Single View Refractive Index Tomography with Neural Fields—0
LightNeuS: Neural Surface Reconstruction in Endoscopy using Illumination DeclineCode0
Sparse 3D Reconstruction via Object-Centric Ray SamplingCode0
SADIR: Shape-Aware Diffusion Models for 3D Image Reconstruction—0
Dense Voxel 3D Reconstruction Using a Monocular Event Camera—0
On the Localization of Ultrasound Image Slices within Point Distribution ModelsCode0
R3D3: Dense 3D Reconstruction of Dynamic Scenes from Multiple Cameras—0
Sparse3D: Distilling Multiview-Consistent Diffusion for Object Reconstruction from Sparse Views—0
Multi-plane denoising diffusion-based dimensionality expansion for 2D-to-3D reconstruction of microstructures with harmonized sampling—0
HoloPOCUS: Portable Mixed-Reality 3D Ultrasound Tracking, Reconstruction and Overlay—0
Textureless Deformable Surface Reconstruction with Invisible Markers—0
Improving NeRF Quality by Progressive Camera Placement for Unrestricted Navigation in Complex Environments—0
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All datasetsDTUShapeNetData3D−R2N2Scan2CAD3DPeopleAria Digital Twin DatasetAria Synthetic EnvironmentsScanNet

Benchmark Results

#ModelMetricClaimedVerifiedStatus
13D-R2N2Overall0.63—Unverified
2GipumaOverall0.58—Unverified
3COLMAPOverall0.53—Unverified
4MVSNetOverall0.46—Unverified
5Vis-MVSNetOverall0.37—Unverified
6AA-RMVSNetOverall0.36—Unverified
7Cas-MVSNetOverall0.36—Unverified
8EPP-MVSNetOverall0.36—Unverified
9PatchmatchNetOverall0.35—Unverified
10CVP-MVSNetOverall0.35—Unverified
#ModelMetricClaimedVerifiedStatus
1MD-GONIoU92.8—Unverified
2POCOIoU92.6—Unverified
3FS-SDFIoU91.2—Unverified
4DP-ConvONetIoU89.5—Unverified
5ConvONetIoU88.4—Unverified
6ONetIoU76.1—Unverified
7EVolTIoU73.8—Unverified
8ZubicLioIoU65.43—Unverified
#ModelMetricClaimedVerifiedStatus
1AttSets3DIoU0.64—Unverified
2PSGN3DIoU0.64—Unverified
3OGN3DIoU0.6—Unverified
43D-R2N23DIoU0.56—Unverified
#ModelMetricClaimedVerifiedStatus
1Scan2CADAverage Accuracy31.68—Unverified
23DMatchAverage Accuracy10.29—Unverified
#ModelMetricClaimedVerifiedStatus
1SVCPChamfer10—Unverified
#ModelMetricClaimedVerifiedStatus
1EVLAccuracy18.2—Unverified
#ModelMetricClaimedVerifiedStatus
1EVLAccuracy5.7—Unverified
#ModelMetricClaimedVerifiedStatus
1Atlas (finetuned)3DIoU89.4—Unverified