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 61–70 of 93 papers

Title	Date	Tasks	Status
Unsupervised Learning on 3D Point Clouds by Clustering and Contrasting	Feb 5, 2022	3D Object ClassificationClustering	—Unverified
Unsupervised Contrastive Learning with Simple Transformation for 3D Point Cloud Data	Oct 13, 2021	3D Object ClassificationClassification	—Unverified
Data-Free Point Cloud Network for 3D Face Recognition	Nov 12, 2019	3D Object ClassificationFace Recognition	—Unverified
Cross-Level Cross-Scale Cross-Attention Network for Point Cloud Representation	Apr 27, 2021	3D Object ClassificationPoint Cloud Segmentation	—Unverified
PointCMC: Cross-Modal Multi-Scale Correspondences Learning for Point Cloud Understanding	Nov 22, 2022	3D Object ClassificationRepresentation Learning	—Unverified
Point Discriminative Learning for Data-efficient 3D Point Cloud Analysis	Aug 4, 2021	3D Object Classification3D Part Segmentation	—Unverified
Point-GR: Graph Residual Point Cloud Network for 3D Object Classification and Segmentation	Dec 4, 2024	3D Object ClassificationClassification	—Unverified
Continual Learning in 3D Point Clouds: Employing Spectral Techniques for Exemplar Selection	Sep 12, 2024	3D Object ClassificationClustering	—Unverified
ClusterNet: Deep Hierarchical Cluster Network With Rigorously Rotation-Invariant Representation for Point Cloud Analysis	Jun 1, 2019	3D Object Classification3D Object Recognition	—Unverified
LATFormer: Locality-Aware Point-View Fusion Transformer for 3D Shape Recognition	Sep 3, 2021	3D Object Classification3D Object Retrieval	—Unverified

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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