Few-Shot 3D Point Cloud Classification

Few-Shot 3D Point Cloud Classification is an advanced computer vision technique aimed at achieving efficient classification of 3D point cloud data with a limited number of samples. This technology leverages deep learning models to enhance their generalization ability and recognition accuracy under conditions of scarce training data, finding extensive applications in fields such as autonomous driving, robotic navigation, and industrial inspection, where it holds significant practical value.