#point cloud analysis

PointMamba offers a state space model for point cloud analysis, using space-filling curves and a Mamba encoder to enhance performance and reduce computational expense. This approach underscores the potential of state space models in 3D vision applications and serves as a strong foundation for ongoing research.

This open-source framework leverages PyTorch Geometric and Facebook Hydra to facilitate the deployment of deep learning models on 3D point cloud data. It supports model development with features like mixed precision training, high-level API access, and methods including PointNet and PVCNN for tasks such as segmentation and object detection. The framework offers a streamlined setup process with Docker and supports diverse datasets such as ScanNet and ModelNet.