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 781–790 of 2326 papers

Title	Date	Tasks	Status	Score
Heightmap Reconstruction of Macula on Color Fundus Images Using Conditional Generative Adversarial Networks	Sep 3, 2020	3D ReconstructionMedical Diagnosis	CodeCode Available	5
GraphX-Convolution for Point Cloud Deformation in 2D-to-3D Conversion	Nov 15, 2019	3D ReconstructionObject	CodeCode Available	5
Graph-Based Parallel Large Scale Structure from Motion	Dec 23, 2019	3D ReconstructionClustering	CodeCode Available	5
Dehazing Cost Volume for Deep Multi-view Stereo in Scattering Media with Airlight and Scattering Coefficient Estimation	Nov 18, 2020	3D ReconstructionDepth Estimation	CodeCode Available	5
DeepVoxels: Learning Persistent 3D Feature Embeddings	Dec 3, 2018	3D ReconstructionNovel View Synthesis	CodeCode Available	5
HarmonicNeRF: Geometry-Informed Synthetic View Augmentation for 3D Scene Reconstruction in Driving Scenarios	Oct 9, 2023	3D Reconstruction3D Scene Reconstruction	CodeCode Available	5
Geo-Supervised Visual Depth Prediction	Jul 30, 2018	3D ReconstructionDepth Estimation	CodeCode Available	5
Deep Stereo using Adaptive Thin Volume Representation with Uncertainty Awareness	Nov 27, 2019	3D ReconstructionPoint Clouds	CodeCode Available	5
DeepPatent2: A Large-Scale Benchmarking Corpus for Technical Drawing Understanding	Nov 7, 2023	3D ReconstructionBenchmarking	CodeCode Available	5
Deep NRSfM++: Towards Unsupervised 2D-3D Lifting in the Wild	Jan 27, 2020	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