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 51–60 of 93 papers

Title	Date	Tasks	Status
Fast Sparse 3D Convolution Network with VDB	Nov 5, 2023	3D Object Classification	—Unverified
Efficient Spatio-Temporal Signal Recognition on Edge Devices Using PointLCA-Net	Nov 21, 2024	3D Object ClassificationComputational Efficiency	—Unverified
3D Object Classification via Spherical Projections	Dec 12, 2017	3D Classification3D Object Classification	—Unverified
Dense Graph Convolutional Neural Networks on 3D Meshes for 3D Object Segmentation and Classification	Jun 30, 2021	3D Object ClassificationDescriptive	—Unverified
MIRACLE 3D: Memory-efficient Integrated Robust Approach for Continual Learning on Point Clouds via Shape Model construction	Oct 8, 2024	3D Object ClassificationContinual Learning	—Unverified
Multi-Task, Multi-Channel, Multi-Input Learning for Mental Illness Detection using Social Media Text	Nov 1, 2019	3D Object ClassificationMulti-class Classification	—Unverified
MVImgNet: A Large-scale Dataset of Multi-view Images	Mar 10, 2023	3D Object ClassificationAttribute	—Unverified
Deep 2.5D Vehicle Classification with Sparse SfM Depth Prior for Automated Toll Systems	May 9, 2018	3D Object ClassificationClassification	—Unverified
Unsupervised 3D Object Learning through Neuron Activity aware Plasticity	Feb 22, 2023	3D Object ClassificationObject	—Unverified
Octree guided CNN with Spherical Kernels for 3D Point Clouds	Feb 28, 2019	3D Object Classification3D Part Segmentation	—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