Point Cloud Mamba: Point Cloud Learning via State Space Model
May 30, 2024 ยท View on GitHub
Point Cloud Mamba: Point Cloud Learning via State Space Model
Tao Zhang, Xiangtai Li*, Haobo Yuan, Shunping Ji, Shuicheng Yan
News
- All codes and weights are available.
Features
- PCM introduces Mamba to point cloud analysis.
- PCM can perform global modeling while maintaining linear computational complexity.
- PCM outperforms PointNeXt on the ScanObjectNN, ModelNet40, and ShapeNetPart datasets.
Install
See Installation Instructions.
Getting Started
See Preparing Datasets for PCM.
Demos
ShapeNetPart
Performance
3-D Point Cloud Classification
3-D Point Cloud Segmentation
@article{zhang2024point,
title={Point Cloud Mamba: Point Cloud Learning via State Space Model},
author={Zhang, Tao and Li, Xiangtai and Yuan, Haobo and Ji, Shunping and Yan, Shuicheng},
journal={arXiv preprint arXiv:2403.00762},
year={2024}
}
Acknowledgement
This repo is based on PointNeXt, PointMLP, Mamba, Vim, and Pontcept. Thanks for their excellent works.