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 11–20 of 93 papers

Title	Date	Tasks	Status	Hype
Block Coordinate Descent for Sparse NMF	Jan 15, 2013	3D Object Classification	CodeCode Available	1
Learning Geometry-Disentangled Representation for Complementary Understanding of 3D Object Point Cloud	Dec 20, 2020	3D Object Classification3D Part Segmentation	CodeCode Available	1
Exploiting Inductive Bias in Transformer for Point Cloud Classification and Segmentation	Apr 27, 2023	3D Object Classification3D Part Segmentation	CodeCode Available	1
diffConv: Analyzing Irregular Point Clouds with an Irregular View	Nov 29, 2021	3D Object Classification3D Point Cloud Classification	CodeCode Available	1
DC3DO: Diffusion Classifier for 3D Objects	Aug 13, 2024	3D Object ClassificationClassification	CodeCode Available	1
Open-Pose 3D Zero-Shot Learning: Benchmark and Challenges	Dec 12, 2023	3D Object ClassificationClassification	CodeCode Available	1
Cascaded Refinement Network for Point Cloud Completion with Self-supervision	Oct 17, 2020	3D Object ClassificationPoint Cloud Completion	CodeCode Available	1
Extending Multi-modal Contrastive Representations	Oct 13, 2023	3D Object ClassificationRepresentation Learning	CodeCode Available	1
Data Augmentation-free Unsupervised Learning for 3D Point Cloud Understanding	Oct 6, 2022	3D Object ClassificationContrastive Learning	CodeCode Available	1
MATE: Masked Autoencoders are Online 3D Test-Time Learners	Nov 21, 2022	3D Object ClassificationPoint Cloud Classification	CodeCode Available	1

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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