3D point cloud segmentation with few examples using shared geometric components with GFS-3DSeg_GWs
3D point cloud segmentation with few examples using shared geometric components with GFS-3DSeg_GWs
Generalized Few-Shot Point Cloud Segmentation Via Geometric Words
arXiv paper abstract https://arxiv.org/abs/2309.11222
arXiv PDF paper https://arxiv.org/pdf/2309.11222.pdf
Existing fully-supervised point cloud segmentation methods suffer in the dynamic testing environment with emerging new classes.
Few-shot point cloud segmentation algorithms address this problem by learning to adapt to new classes at the sacrifice of segmentation accuracy for the base classes, which severely impedes its practicality.
... present ... generalized few-shot point cloud segmentation, which requires the model to generalize to new categories with only a few support point clouds and simultaneously retain the capability to segment base classes.
... propose the geometric words to represent geometric components shared between the base and novel classes, and incorporate them into a novel geometric-aware semantic representation to facilitate better generalization to the new classes without forgetting the old ones.
... introduce geometric prototypes to guide the segmentation with geometric prior knowledge.
... illustrate the superior performance of ... method over baseline methods ...
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