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 2126–2150 of 2326 papers

TitleStatusHype
DirectL: Efficient Radiance Fields Rendering for 3D Light Field Displays—0
Direct Structure Estimation for 3D Reconstruction—0
Discrete Laplace Operator Estimation for Dynamic 3D Reconstruction—0
Discrete Optimization of Ray Potentials for Semantic 3D Reconstruction—0
Discriminative training of conditional random fields with probably submodular constraints—0
Disentangling 3D Attributes from a Single 2D Image: Human Pose, Shape and Garment—0
SurgicalGS: Dynamic 3D Gaussian Splatting for Accurate Robotic-Assisted Surgical Scene Reconstruction—0
Disparity-Augmented Trajectories for Human Activity Recognition—0
Dispersed Structured Light for Hyperspectral 3D Imaging—0
Distillation of Diffusion Features for Semantic Correspondence—0
Distributed Bundle Adjustment—0
SurgPointTransformer: Vertebrae Shape Completion with RGB-D Data—0
DiViNeT: 3D Reconstruction from Disparate Views via Neural Template Regularization—0
SurGSplat: Progressive Geometry-Constrained Gaussian Splatting for Surgical Scene Reconstruction—0
DnD: Dense Depth Estimation in Crowded Dynamic Indoor Scenes—0
A Generative Machine Learning Model for Material Microstructure 3D Reconstruction and Performance Evaluation—0
D-OccNet: Detailed 3D Reconstruction Using Cross-Domain Learning—0
A Generative Approach to High Fidelity 3D Reconstruction from Text Data—0
Domain Adaptation for Real-World Single View 3D Reconstruction—0
Domain adaptation strategies for 3D reconstruction of the lumbar spine using real fluoroscopy data—0
Doppelgangers++: Improved Visual Disambiguation with Geometric 3D Features—0
Volumetric Reconstruction of Prostatectomy Specimens from Histology—0
Do We Need Binary Features for 3D Reconstruction?—0
DreamGrasp: Zero-Shot 3D Multi-Object Reconstruction from Partial-View Images for Robotic Manipulation—0
DreaMo: Articulated 3D Reconstruction From A Single Casual Video—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