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 1061–1070 of 2326 papers

Title	Date	Tasks	Status
Efficient Global Optimization of Non-differentiable, Symmetric Objectives for Multi Camera Placement	Mar 20, 2021	3D Reconstructionglobal-optimization	—Unverified
Efficient and Robust Training of Dense Object Nets for Multi-Object Robot Manipulation	Jun 24, 2022	3D ReconstructionObject	—Unverified
Black-Box Test-Time Shape REFINEment for Single View 3D Reconstruction	Aug 23, 2021	3D ReconstructionSingle-View 3D Reconstruction	—Unverified
Active Neural 3D Reconstruction with Colorized Surface Voxel-based View Selection	May 4, 2024	3D Reconstruction3D Scene Reconstruction	—Unverified
Efficient 3D Room Shape Recovery From a Single Panorama	Jun 1, 2016	3D ReconstructionSuperpixels	—Unverified
Efficient 3D Reconstruction, Streaming and Visualization of Static and Dynamic Scene Parts for Multi-client Live-telepresence in Large-scale Environments	Nov 25, 2022	3D Reconstruction	—Unverified
Effective Rank Analysis and Regularization for Enhanced 3D Gaussian Splatting	Jun 17, 2024	3DGS3D Reconstruction	—Unverified
Edge Projection-Based Adaptive View Selection for Cone-Beam CT	Jul 17, 2024	3D ReconstructionComputed Tomography (CT)	—Unverified
Biomass phenotyping of oilseed rape through UAV multi-view oblique imaging with 3DGS and SAM model	Nov 13, 2024	3DGS3D Reconstruction	—Unverified
3D Reconstruction in Noisy Agricultural Environments: A Bayesian Optimization Perspective for View Planning	Sep 29, 2023	3D ReconstructionBayesian Optimization	—Unverified

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All datasets DTU ShapeNet Data3D−R2N2 Scan2CAD 3DPeople Aria Digital Twin Dataset Aria Synthetic Environments ScanNet

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	3D-R2N2	Overall	0.63	—	Unverified
2	Gipuma	Overall	0.58	—	Unverified
3	COLMAP	Overall	0.53	—	Unverified
4	MVSNet	Overall	0.46	—	Unverified
5	Vis-MVSNet	Overall	0.37	—	Unverified
6	AA-RMVSNet	Overall	0.36	—	Unverified
7	Cas-MVSNet	Overall	0.36	—	Unverified
8	EPP-MVSNet	Overall	0.36	—	Unverified
9	PatchmatchNet	Overall	0.35	—	Unverified
10	CVP-MVSNet	Overall	0.35	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MD-GON	IoU	92.8	—	Unverified
2	POCO	IoU	92.6	—	Unverified
3	FS-SDF	IoU	91.2	—	Unverified
4	DP-ConvONet	IoU	89.5	—	Unverified
5	ConvONet	IoU	88.4	—	Unverified
6	ONet	IoU	76.1	—	Unverified
7	EVolT	IoU	73.8	—	Unverified
8	ZubicLio	IoU	65.43	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	AttSets	3DIoU	0.64	—	Unverified
2	PSGN	3DIoU	0.64	—	Unverified
3	OGN	3DIoU	0.6	—	Unverified
4	3D-R2N2	3DIoU	0.56	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Scan2CAD	Average Accuracy	31.68	—	Unverified
2	3DMatch	Average Accuracy	10.29	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SVCP	Chamfer	10	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	EVL	Accuracy	18.2	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	EVL	Accuracy	5.7	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Atlas (finetuned)	3DIoU	89.4	—	Unverified