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View all- Fayjie ALens MVandewalle P(2025)Few-Shot Segmentation of 3D Point Clouds Under Real-World Distributional Shifts in Railroad InfrastructureSensors10.3390/s2504107225:4(1072)Online publication date: 11-Feb-2025
Semantic Segmentation for 3D point clouds has made great progress in recent years. Most existing approaches for 3D point cloud segmentation are fully supervised, and they require a large number of well-annotated data for training. The training data is ...
Recently, few-shot 3D point cloud semantic segmentation methods have been introduced to mitigate the limitations of existing fully supervised approaches, i.e., heavy dependence on labeled 3D data and poor capacity to generalize to new categories. ...
3D point cloud semantic segmentation is one of the fundamental tasks for 3D scene understanding and has been widely used in the metaverse applications. Many recent 3D semantic segmentation methods learn a single prototype (classifier weights) for ...
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