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
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
Primitive3D: 3D Object Dataset Synthesis from Randomly Assembled Primitives	May 25, 2022	3D Object ClassificationDataset Distillation	—Unverified
Real-time object detection and tracking using flash LiDAR imagery	Jun 7, 2024	3D Object ClassificationObject	—Unverified
RW-Net: Enhancing Few-Shot Point Cloud Classification with a Wavelet Transform Projection-based Network	Jan 6, 2025	3D Object ClassificationFew-Shot Learning	—Unverified
Self-Supervised Multi-View Learning via Auto-Encoding 3D Transformations	Mar 1, 2021	3D Object Classification3D Object Recognition	—Unverified
Sim2Real 3D Object Classification using Spherical Kernel Point Convolution and a Deep Center Voting Scheme	Mar 10, 2021	3D Object ClassificationGeneral Classification	—Unverified
Spherical Convolutional Neural Network for 3D Point Clouds	May 21, 2018	3D Object ClassificationGeneral Classification	—Unverified
Spherical Fractal Convolutional Neural Networks for Point Cloud Recognition	Jun 1, 2019	3D Object Classification3D Part Segmentation	—Unverified
Spherical Transformer: Adapting Spherical Signal to CNNs	Jan 11, 2021	3D Object ClassificationGeneral Classification	—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