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 911–920 of 2326 papers

Title	Date	Tasks	Status	Hype
Two-stage Synthetic Supervising and Multi-view Consistency Self-supervising based Animal 3D Reconstruction by Single Image	Nov 22, 2023	3D ReconstructionSingle-View 3D Reconstruction	CodeCode Available	0
Differentiable Radio Frequency Ray Tracing for Millimeter-Wave Sensing	Nov 22, 2023	3D Reconstruction	—Unverified	0
Robustifying Generalizable Implicit Shape Networks with a Tunable Non-Parametric Model	Nov 21, 2023	3D ReconstructionPoint cloud reconstruction	CodeCode Available	0
Physics-guided Shape-from-Template: Monocular Video Perception through Neural Surrogate Models	Nov 21, 2023	3D Reconstruction	CodeCode Available	1
Mixing-Denoising Generalizable Occupancy Networks	Nov 20, 2023	3D ReconstructionDecoder	—Unverified	0
PF-LRM: Pose-Free Large Reconstruction Model for Joint Pose and Shape Prediction	Nov 20, 2023	3D ReconstructionGPU	—Unverified	0
GaussianDiffusion: 3D Gaussian Splatting for Denoising Diffusion Probabilistic Models with Structured Noise	Nov 19, 2023	3D Generation3D Reconstruction	—Unverified	0
LOSTU: Fast, Scalable, and Uncertainty-Aware Triangulation	Nov 18, 2023	3D ReconstructionPose Estimation	—Unverified	0
Invariant-based Mapping of Space During General Motion of an Observer	Nov 18, 2023	3D ReconstructionOptical Flow Estimation	—Unverified	0
Structure-Aware Sparse-View X-ray 3D Reconstruction	Nov 18, 2023	3D ReconstructionCT Reconstruction	CodeCode Available	5

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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