3D Object Classification

3D Object Classification is the task of predicting the class of a 3D object point cloud. It is a voxel level prediction where each voxel is classified into a category. The popular benchmark for this task is the ModelNet dataset. The models for this task are usually evaluated with the Classification Accuracy metric.

Image: Sedaghat et al

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 41–50 of 93 papers

Title	Date	Tasks	Status	Score
Learning a Hierarchical Latent-Variable Model of 3D Shapes	May 17, 2017	3D Object Classification3D Object Recognition	CodeCode Available	5
MeshCNN: A Network with an Edge	Sep 16, 2018	3D Object Classification3D Part Segmentation	CodeCode Available	5
OctNet: Learning Deep 3D Representations at High Resolutions	Nov 15, 2016	3D Object ClassificationGeneral Classification	CodeCode Available	5
On Automatic Data Augmentation for 3D Point Cloud Classification	Dec 11, 2021	3D Object Classification3D Object Recognition	CodeCode Available	5
PaRot: Patch-Wise Rotation-Invariant Network via Feature Disentanglement and Pose Restoration	Feb 6, 2023	3D Object ClassificationDisentanglement	CodeCode Available	5
RotationNet: Joint Object Categorization and Pose Estimation Using Multiviews from Unsupervised Viewpoints	Mar 20, 2016	3D Object ClassificationObject	CodeCode Available	5
Spherical Kernel for Efficient Graph Convolution on 3D Point Clouds	Sep 20, 2019	3D Instance Segmentation3D Object Classification	CodeCode Available	5
L3DOC: Lifelong 3D Object Classification	Dec 12, 2019	3D geometry3D Object Classification	—Unverified	0
Spherical Transformer: Adapting Spherical Signal to CNNs	Jan 11, 2021	3D Object ClassificationGeneral Classification	—Unverified	0
SPNet: Deep 3D Object Classification and Retrieval using Stereographic Projection	Nov 5, 2018	3D Object ClassificationClassification	—Unverified	0

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All datasets ModelNet40 ModelNet10 3R-Scan Remote Flash LiDAR Vehicles Dataset

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	Ours	Classification Accuracy	93.6	—	Unverified
2	G3DNet-18 MLP, Fine-Tuned, Vote	Classification Accuracy	91.7	—	Unverified
3	CrossMoCo	Classification Accuracy	91.49	—	Unverified
4	O-CNN(6)	Classification Accuracy	89.9	—	Unverified
5	Spherical Kernel	Classification Accuracy	89.3	—	Unverified
6	3D-PointCapsNet	Classification Accuracy	89.3	—	Unverified
7	ECC (12 votes)	Classification Accuracy	83.2	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	PolyNet	Accuracy	94.93	—	Unverified
2	ORION	Accuracy	93.8	—	Unverified
3	G3DNet-18 SVM, Fine-Tuned, Vote	Accuracy	93.1	—	Unverified
4	ECC (12 votes)	Accuracy	90	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SceneGraphFusion	Top-10 Accuracy	0.8	—	Unverified
2	3DSSG [Wald2020_3dssg]	Top-10 Accuracy	0.78	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	YOLO-X	mean average precision	0.99	—	Unverified