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 931–940 of 2326 papers

Title	Date	Tasks	Status
Improving 3D Finger Traits Recognition via Generalizable Neural Rendering	Oct 12, 2024	3D geometry3D Reconstruction	—Unverified
Neurally Integrated Finite Elements for Differentiable Elasticity on Evolving Domains	Oct 12, 2024	3D ReconstructionNumerical Integration	—Unverified
Ego3DT: Tracking Every 3D Object in Ego-centric Videos	Oct 11, 2024	3D Reconstruction3D Scene Reconstruction	—Unverified
SurgicalGS: Dynamic 3D Gaussian Splatting for Accurate Robotic-Assisted Surgical Scene Reconstruction	Oct 11, 2024	3D geometry3D Reconstruction	—Unverified
MPF-GAN: an enhanced architecture for 3D face reconstruction	Oct 10, 2024	3D Face Reconstruction3D Reconstruction	CodeCode Available
FusionSense: Bridging Common Sense, Vision, and Touch for Robust Sparse-View Reconstruction	Oct 10, 2024	3D ReconstructionCommon Sense Reasoning	—Unverified
UW-SDF: Exploiting Hybrid Geometric Priors for Neural SDF Reconstruction from Underwater Multi-view Monocular Images	Oct 10, 2024	3D ReconstructionNeural Rendering	—Unverified
Fine-detailed Neural Indoor Scene Reconstruction using multi-level importance sampling and multi-view consistency	Oct 10, 2024	3D ReconstructionIndoor Scene Reconstruction	—Unverified
3D Vision-Language Gaussian Splatting	Oct 10, 2024	3D ReconstructionAutonomous Driving	—Unverified
3D2M Dataset: A 3-Dimension diverse Mesh Dataset	Oct 9, 2024	3D ReconstructionDiversity	CodeCode Available

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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