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 1591–1600 of 2326 papers

Title	Date	Tasks	Status
H4D: Human 4D Modeling by Learning Neural Compositional Representation	Mar 2, 2022	3D ReconstructionFuture prediction	—Unverified
Object Pose Estimation using Mid-level Visual Representations	Mar 2, 2022	3D ReconstructionObject	CodeCode Available
3D object reconstruction and 6D-pose estimation from 2D shape for robotic grasping of objects	Mar 2, 2022	3D Object Reconstruction3D Reconstruction	—Unverified
ONIX: an X-ray deep-learning tool for 3D reconstructions from sparse views	Mar 1, 2022	3D Object Reconstruction3D Reconstruction	—Unverified
Large-Scale 3D Semantic Reconstruction for Automated Driving Vehicles with Adaptive Truncated Signed Distance Function	Feb 28, 2022	3D Reconstruction	—Unverified
ERF: Explicit Radiance Field Reconstruction From Scratch	Feb 28, 2022	3D Reconstruction	—Unverified
RelMobNet: End-to-end relative camera pose estimation using a robust two-stage training	Feb 25, 2022	3D ReconstructionCamera Pose Estimation	—Unverified
N-QGN: Navigation Map from a Monocular Camera using Quadtree Generating Networks	Feb 24, 2022	3D ReconstructionAutonomous Navigation	—Unverified
On Monocular Depth Estimation and Uncertainty Quantification using Classification Approaches for Regression	Feb 24, 2022	3D ReconstructionAutonomous Driving	—Unverified
MITI: SLAM Benchmark for Laparoscopic Surgery	Feb 23, 2022	3D Reconstruction	—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