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 2201–2250 of 2326 papers

TitleStatusHype
Flight Dynamics-based Recovery of a UAV Trajectory using Ground Cameras—0
Social Behavior Prediction from First Person Videos—0
3D Reconstruction of Heterogeneous Virus Particles with Statistical Geometric Symmetry—0
Semi-Dense 3D Semantic Mapping from Monocular SLAM—0
De-noising, Stabilizing and Completing 3D Reconstructions On-the-go using Plane Priors—0
Target-driven Visual Navigation in Indoor Scenes using Deep Reinforcement LearningCode0
ORBSLAM-based Endoscope Tracking and 3D Reconstruction—0
Unconstrained Two-parallel-plane Model for Focused Plenoptic Cameras Calibration—0
Branching Gaussian Processes with Applications to Spatiotemporal Reconstruction of 3D Trees—0
Feature Descriptors for Tracking by Detection: a Benchmark—0
Multi-body Non-rigid Structure-from-Motion—0
Boundary conditions for Shape from Shading—0
A Representation Theory Perspective on Simultaneous Alignment and Classification—0
Automatic 3D Reconstruction for Symmetric Shapes—0
3DFS: Deformable Dense Depth Fusion and Segmentation for Object Reconstruction from a Handheld Camera—0
Multicamera Calibration From Visible and Mirrored Epipoles—0
Spatiotemporal Bundle Adjustment for Dynamic 3D Reconstruction—0
3D Reconstruction of Transparent Objects With Position-Normal Consistency—0
Inextensible Non-Rigid Shape-From-Motion by Second-Order Cone Programming—0
Piecewise-Planar 3D Approximation From Wide-Baseline Stereo—0
Unbiased Photometric Stereo for Colored Surfaces: A Variational Approach—0
Automated 3D Face Reconstruction From Multiple Images Using Quality Measures—0
Multiview Rectification of Folded Documents—0
Sparse to Dense 3D Reconstruction From Rolling Shutter Images—0
Patches, Planes and Probabilities: A Non-Local Prior for Volumetric 3D Reconstruction—0
Efficient 3D Room Shape Recovery From a Single Panorama—0
Structure-From-Motion RevisitedCode0
Large-Scale Semantic 3D Reconstruction: An Adaptive Multi-Resolution Model for Multi-Class Volumetric Labeling—0
Self-expressive Dictionary Learning for Dynamic 3D Reconstruction—0
UAV-based Autonomous Image Acquisition with Multi-View Stereo Quality Assurance by Confidence Prediction—0
Multiview Differential Geometry of Curves—0
Automatic 3D Reconstruction of Manifold Meshes via Delaunay Triangulation and Mesh Sweeping—0
Unsupervised single-particle deep clustering via statistical manifold learning—0
Semantic 3D Reconstruction with Continuous Regularization and Ray Potentials Using a Visibility Consistency ConstraintCode0
Geometric Scene Parsing with Hierarchical LSTM—0
SMASH: Physics-guided Reconstruction of Collisions from VideosCode0
An Approach for Noise Removal on Depth Images—0
Do We Need Binary Features for 3D Reconstruction?—0
Virtual Rephotography: Novel View Prediction Error for 3D Reconstruction—0
On the Diagnostic of Road Pathway Visibility—0
Multistage SFM: A Coarse-to-Fine Approach for 3D Reconstruction—0
3D Reconstruction of Crime Scenes and Design Considerations for an Interactive Investigation Tool—0
Exploiting Object Similarity in 3D Reconstruction—0
Exploiting High Level Scene Cues in Stereo Reconstruction—0
Structure From Motion Using Structure-Less Resection—0
Single-View Reconstruction via Joint Analysis of Image and Shape CollectionsCode0
Massively Parallel Multiview Stereopsis by Surface Normal DiffusionCode0
Photometric Stereo in a Scattering Medium—0
Sparse Dynamic 3D Reconstruction From Unsynchronized Videos—0
High Quality Structure From Small Motion for Rolling Shutter Cameras—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