Weakly Supervised 3D Point Cloud Segmentation

The Chinese text provided can be translated into English as follows: "Weakly Supervised 3D Point Cloud Segmentation is a technique in the field of computer vision aimed at segmenting 3D point clouds with limited labeled data. This method leverages weak labels or incomplete labels to reduce annotation costs and improve the model's generalization ability. Its goal is to accurately identify and classify different objects or regions within the point cloud, and it has significant application value in scenarios such as autonomous driving, robotic navigation, and virtual reality."