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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