Region-Transformer: Self-Attention Region Based Class-Agnostic Point Cloud Segmentation

arXiv:2403.01407v1 Announce Type: new
Abstract: Point cloud segmentation, which helps us understand the environment of specific structures and objects, can be performed in class-specific and class-agnostic ways. We propose a novel region-based transformer model called Region-Transformer for performing class-agnostic point cloud segmentation. The model utilizes a region-growth approach and self-attention mechanism to iteratively expand or contract a region by adding or removing points. It is trained on simulated point clouds with instance labels only, avoiding semantic labels. Attention-based networks have …

abstract arxiv attention class cloud cs.ai cs.cv cs.ro environment growth novel objects segmentation self-attention the environment transformer transformer model type