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 1826–1850 of 2326 papers

TitleStatusHype
Method for the generation of depth images for view-based shape retrieval of 3D CAD model from partial point cloud—0
Joint Hand-object 3D Reconstruction from a Single Image with Cross-branch Feature Fusion—0
On the generalization of learning-based 3D reconstruction—0
Set Distribution Networks: a Generative Model for Sets of Images—0
Wireless 3D Point Cloud Delivery Using Deep Graph Neural Networks—0
Geodesic-HOF: 3D Reconstruction Without Cutting Corners—0
3D Reconstruction of Clothes using a Human Body Model and its Application to Image-based Virtual Try-On—0
FroDO: From Detections to 3D Objects—0
Joint Texture and Geometry Optimization for RGB-D Reconstruction—0
Mapillary Street-Level Sequences: A Dataset for Lifelong Place Recognition—0
Three-Dimensional Reconstruction of Human Interactions—0
An Efficient Planar Bundle Adjustment Algorithm—0
D2D: Keypoint Extraction with Describe to Detect Approach—0
Deep Learning Guided Building Reconstruction from Satellite Imagery-derived Point Clouds—0
FroDO: From Detections to 3D Objects—0
A Simple and Scalable Shape Representation for 3D Reconstruction—0
Multi-view data capture using edge-synchronised mobiles—0
Stomach 3D Reconstruction Based on Virtual Chromoendoscopic Image Generation—0
Reconstruct, Rasterize and Backprop: Dense shape and pose estimation from a single image—0
The Covering-Assignment Problem for Swarm-powered Ad-hoc Clouds: A Distributed 3D Mapping Use-caseCode0
Robust 3D reconstruction of dynamic scenes from single-photon lidar using Beta-divergences—0
Calculating Pose with Vanishing Points of Visual-Sphere Perspective Model—0
ARCH: Animatable Reconstruction of Clothed HumansCode0
Differential 3D Facial Recognition: Adding 3D to Your State-of-the-Art 2D Method—0
End-To-End Convolutional Neural Network for 3D Reconstruction of Knee Bones From Bi-Planar X-Ray Images—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