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 1–10 of 93 papers

Title	Date	Tasks	Status	Hype
PointLLM: Empowering Large Language Models to Understand Point Clouds	Aug 31, 2023	3D Object Captioning3D Object Classification	CodeCode Available	2
CrossPoint: Self-Supervised Cross-Modal Contrastive Learning for 3D Point Cloud Understanding	Mar 1, 2022	3D Object Classification3D Point Cloud Linear Classification	CodeCode Available	2
PCP-MAE: Learning to Predict Centers for Point Masked Autoencoders	Aug 16, 2024	3D Object Classification3D Point Cloud Classification	CodeCode Available	2
Uni3D: Exploring Unified 3D Representation at Scale	Oct 10, 2023	3D Object ClassificationRetrieval	CodeCode Available	2
MiniGPT-3D: Efficiently Aligning 3D Point Clouds with Large Language Models using 2D Priors	May 2, 2024	3D Object Captioning3D Object Classification	CodeCode Available	2
Exploiting Inductive Bias in Transformer for Point Cloud Classification and Segmentation	Apr 27, 2023	3D Object Classification3D Part Segmentation	CodeCode Available	1
Open-Pose 3D Zero-Shot Learning: Benchmark and Challenges	Dec 12, 2023	3D Object ClassificationClassification	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
DC3DO: Diffusion Classifier for 3D Objects	Aug 13, 2024	3D Object ClassificationClassification	CodeCode Available	1

Show:10 25 50

← PrevPage 1 of 10Next →

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