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 Added Most Hyped Most Active Needs Verification Most Verified

Showing 1231–1240 of 2326 papers

Title	Date	Tasks	Status
Integration of the 3D Environment for UAV Onboard Visual Object Tracking	Aug 6, 2020	3D ReconstructionObject	—Unverified
Integration of Absolute Orientation Measurements in the KinectFusion Reconstruction pipeline	Feb 12, 2018	3D ReconstructionGPU	—Unverified
Intensity Video Guided 4D Fusion for Improved Highly Dynamic 3D Reconstruction	Aug 6, 2017	3D Reconstruction	—Unverified
Interaction-Driven Active 3D Reconstruction with Object Interiors	Oct 23, 2023	3D ReconstructionActive 3D Reconstruction	—Unverified
Interactive Manipulation and Visualization of 3D Brain MRI for Surgical Training	Mar 24, 2024	3D Reconstruction	—Unverified
A Brief Survey of Image Processing Algorithms in Electrical Capacitance Tomography	Oct 15, 2015	3D Reconstruction	—Unverified
In-the-Wild Single Camera 3D Reconstruction Through Moving Water Surfaces	Jan 1, 2021	3D Reconstruction	—Unverified
Invariant-based Mapping of Space During General Motion of an Observer	Nov 18, 2023	3D ReconstructionOptical Flow Estimation	—Unverified
Investigating Spherical Epipolar Rectification for Multi-View Stereo 3D Reconstruction	Apr 8, 2022	3D ReconstructionDisparity Estimation	—Unverified
INV-Flow2PoseNet: Light-Resistant Rigid Object Pose from Optical Flow of RGB-D Images using Images, Normals and Vertices	Sep 14, 2022	3D ReconstructionOptical Flow Estimation	—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