SelectAnyTree: A Promptable Instance Segmentation Model for 3D Forest LiDAR Point Clouds
Instance segmentation of trees in forest LiDAR point clouds is constrained by label scarcity: A single hectare holds millions of points and hundreds of overlapping tree crowns, making manual annotation laborious, while automatic pre-segmentations offer no interactive refinement. Inspired by the promptable paradigm of foundation segmentation models, we propose SelectAnyTree, which delineates any individual tree in a 3D forest point cloud from a few clicks and is purpose-built for promptable instance segmentation of 3D forest LiDAR scenes. The proposed SelectAnyTree couples three lightweight stages: (1) Sparse voxel scene encoder that embeds the forest once into reusable features, (2) Click...
| Authors | Trung Thanh Nguyen, Daniel Lusk, Kilian Gerberding et al. |
|---|---|
| Primary category | cs.CV |
| Published | 25 June 2026 |
| Last updated at source | 27 August 2026 |
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