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

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Showing 81–90 of 93 papers

Title	Date	Tasks	Status
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
FusionNet: 3D Object Classification Using Multiple Data Representations	Jul 19, 2016	3D Object Classification3D Object Recognition	—Unverified
Generalized Multi-view Shared Subspace Learning using View Bootstrapping	May 12, 2020	3D Object ClassificationFace Recognition	—Unverified
Spherical Convolutional Neural Network for 3D Point Clouds	May 21, 2018	3D Object ClassificationGeneral Classification	—Unverified
Generative VoxelNet: Learning Energy-Based Models for 3D Shape Synthesis and Analysis	Dec 25, 2020	3D Object ClassificationSuper-Resolution	—Unverified
Formula-Supervised Visual-Geometric Pre-training	Sep 20, 2024	3D Object Classification3D Object Recognition	—Unverified
GS-PT: Exploiting 3D Gaussian Splatting for Comprehensive Point Cloud Understanding via Self-supervised Learning	Sep 8, 2024	3DGS3D Object Classification	—Unverified
HGNet: Learning Hierarchical Geometry From Points, Edges, and Surfaces	Jan 1, 2023	3D Object ClassificationAll	—Unverified
I3DOL: Incremental 3D Object Learning without Catastrophic Forgetting	Dec 16, 2020	3D Object ClassificationFairness	—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