Transformer-Based Tree Point Cloud Segmentation
Joint semantic and instance segmentation of large-scale tree point clouds with a sparse 3D transformer and hierarchical geometric priors.
A transformer-based framework designed for joint semantic and instance segmentation of large-scale tree point clouds. The approach incorporates hierarchical geometric priors that reflect biological tree structure and employs a sparse 3D transformer to model long-range spatial dependencies. A query-based decoding head enables scalable instance prediction without clustering, offering an efficient solution for forestry-scale 3D understanding.