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 751–760 of 2326 papers

Title	Date	Tasks	Status	Score
Learning Character-Agnostic Motion for Motion Retargeting in 2D	May 5, 2019	3D Reconstructionmotion retargeting	CodeCode Available	5
M3D: Dual-Stream Selective State Spaces and Depth-Driven Framework for High-Fidelity Single-View 3D Reconstruction	Nov 19, 2024	3D ReconstructionAutonomous Driving	CodeCode Available	5
Hybrid coarse-fine classification for head pose estimation	Jan 21, 2019	3D ReconstructionClassification	CodeCode Available	5
HuSc3D: Human Sculpture dataset for 3D object reconstruction	Jun 9, 2025	3D Object Reconstruction3D Reconstruction	CodeCode Available	5
Hyperparameter-Free Losses for Model-Based Monocular Reconstruction	Aug 16, 2019	3D ReconstructionBenchmarking	CodeCode Available	5
Enhanced Encoder-Decoder Architecture for Accurate Monocular Depth Estimation	Oct 15, 2024	3D ReconstructionDecoder	CodeCode Available	5
Hubless keypoint-based 3D deformable groupwise registration	Sep 11, 2018	3D ReconstructionAnatomy	CodeCode Available	5
3DDX: Bone Surface Reconstruction from a Single Standard-Geometry Radiograph via Dual-Face Depth Estimation	Sep 25, 2024	3D ReconstructionComputational Efficiency	CodeCode Available	5
Probabilistic Inference for Camera Calibration in Light Microscopy under Circular Motion	Oct 30, 2019	3D ReconstructionCamera Calibration	CodeCode Available	5
Highlighting objects of interest in an image by integrating saliency and depth	Nov 28, 2017	3D 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