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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 2276–2300 of 2326 papers

TitleStatusHype
MOTChallenge 2015: Towards a Benchmark for Multi-Target TrackingCode0
Lifting Object Detection Datasets into 3D—0
PiMPeR: Piecewise Dense 3D Reconstruction from Multi-View and Multi-Illumination Images—0
Dense image registration and deformable surface reconstruction in presence of occlusions and minimal texture—0
Building with Drones: Accurate 3D Facade Reconstruction using MAVs—0
RANSAC based three points algorithm for ellipse fitting of spherical object's projection—0
Computer-assisted polyp matching between optical colonoscopy and CT colonography: a phantom study—0
Efficient Inference of Continuous Markov Random Fields with Polynomial Potentials—0
Grouping-Based Low-Rank Trajectory Completion and 3D Reconstruction—0
A Framework for the Volumetric Integration of Depth Images—0
MAP Visibility Estimation for Large-Scale Dynamic 3D Reconstruction—0
High Quality Photometric Reconstruction using a Depth Camera—0
Local Readjustment for High-Resolution 3D Reconstruction—0
Robust 3D Features for Matching between Distorted Range Scans Captured by Moving Systems—0
Complex Non-Rigid Motion 3D Reconstruction by Union of Subspaces—0
Photometric Bundle Adjustment for Dense Multi-View 3D ModelingCode0
3D Reconstruction from Accidental Motion—0
Stable Template-Based Isometric 3D Reconstruction in All Imaging Conditions by Linear Least-Squares—0
Energy Based Multi-model Fitting & Matching for 3D Reconstruction—0
The Photometry of Intrinsic Images—0
Critical Configurations For Radial Distortion Self-Calibration—0
Diffuse Mirrors: 3D Reconstruction from Diffuse Indirect Illumination Using Inexpensive Time-of-Flight Sensors—0
Class Specific 3D Object Shape Priors Using Surface Normals—0
Fast and Accurate Image Matching with Cascade Hashing for 3D Reconstruction—0
Turning Mobile Phones into 3D Scanners—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