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 2101–2125 of 2326 papers

TitleStatusHype
Collaborative Large-Scale Dense 3D Reconstruction with Online Inter-Agent Pose Optimisation—0
Domain-Specific Face Synthesis for Video Face Recognition from a Single Sample Per PersonCode0
Deep Learning Reconstruction for 9-View Dual Energy CT Baggage Scanner—0
Geometry Processing of Conventionally Produced Mouse Brain Slice Images—0
Accurate 3D Reconstruction of Dynamic Scenes from Monocular Image Sequences with Severe Occlusions—0
Real-time 3D Reconstruction on Construction Site using Visual SLAM and UAV—0
A Performance Evaluation of Local Features for Image Based 3D Reconstruction—0
An Integrated Platform for Live 3D Human Reconstruction and Motion Capturing—0
Small Drone Field Experiment: Data Collection & Processing—0
Image2Mesh: A Learning Framework for Single Image 3D ReconstructionCode0
Highlighting objects of interest in an image by integrating saliency and depthCode0
Unsupervised 3D Reconstruction from a Single Image via Adversarial Learning—0
3D Reconstruction of Incomplete Archaeological Objects Using a Generative Adversarial NetworkCode0
End-to-end 3D shape inverse rendering of different classes of objects from a single input image—0
MarrNet: 3D Shape Reconstruction via 2.5D Sketches—0
Real-Time Automatic Fetal Brain Extraction in Fetal MRI by Deep LearningCode0
Large-Scale 3D Shape Reconstruction and Segmentation from ShapeNet Core55—0
Semantic 3D Reconstruction with Finite Element Bases—0
Corner-Based Geometric Calibration of Multi-Focus Plenoptic CamerasCode0
3D Surface Detail Enhancement From a Single Normal Map—0
Probabilistic Structure From Motion With Objects (PSfMO)—0
Deltille Grids for Geometric Camera Calibration—0
From Point Clouds to Mesh Using Regression—0
Multi-View Non-Rigid Refinement and Normal Selection for High Quality 3D Reconstruction—0
Practical Projective Structure From Motion (P2SfM)—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