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 2301–2326 of 2326 papers

TitleStatusHype
Single-View 3D Scene Parsing by Attributed Grammar—0
Robust 3D Features for Matching between Distorted Range Scans Captured by Moving Systems—0
Multi-Output Learning for Camera Relocalization—0
Diffuse Mirrors: 3D Reconstruction from Diffuse Indirect Illumination Using Inexpensive Time-of-Flight Sensors—0
Energy Based Multi-model Fitting & Matching for 3D Reconstruction—0
Fast and Accurate Image Matching with Cascade Hashing for 3D Reconstruction—0
Critical Configurations For Radial Distortion Self-Calibration—0
A New Framework for Sign Language Recognition based on 3D Handshape Identification and Linguistic Modeling—0
ROML: A Robust Feature Correspondence Approach for Matching Objects in A Set of Images—0
Simultaneous Super-Resolution of Depth and Images Using a Single Camera—0
Tensor-Based Human Body Modeling—0
Dense 3D Reconstruction from Severely Blurred Images Using a Single Moving Camera—0
Dense Reconstruction Using 3D Object Shape Priors—0
Learning a Manifold as an Atlas—0
Template-Based Isometric Deformable 3D Reconstruction with Sampling-Based Focal Length Self-Calibration—0
Monocular Template-Based 3D Reconstruction of Extensible Surfaces with Local Linear Elasticity—0
Articulated and Restricted Motion Subspaces and Their Signatures—0
A Theory of Refractive Photo-Light-Path Triangulation—0
Joint Detection, Tracking and Mapping by Semantic Bundle Adjustment—0
Joint 3D Scene Reconstruction and Class Segmentation—0
Relative Volume Constraints for Single View 3D Reconstruction—0
Dense Variational Reconstruction of Non-rigid Surfaces from Monocular Video—0
ChESS - Quick and Robust Detection of Chess-board FeaturesCode0
Thompson Sampling: An Asymptotically Optimal Finite Time AnalysisCode0
Autocalibration with the Minimum Number of Cameras with Known Pixel Shape—0
Cascaded Classification Models: Combining Models for Holistic Scene Understanding—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