Mamba3D: Enhancing Local Features for 3D Point Cloud Analysis via State Space Model

arXiv:2404.14966v1 Announce Type: cross
Abstract: Existing Transformer-based models for point cloud analysis suffer from quadratic complexity, leading to compromised point cloud resolution and information loss. In contrast, the newly proposed Mamba model, based on state space models (SSM), outperforms Transformer in multiple areas with only linear complexity. However, the straightforward adoption of Mamba does not achieve satisfactory performance on point cloud tasks. In this work, we present Mamba3D, a state space model tailored for point cloud learning to enhance local …

abstract analysis arxiv cloud complexity contrast cs.ai cs.cv cs.lg features information linear loss mamba multiple resolution space ssm state state space model state space models transformer transformer-based models type via