Point Cloud Segmentation is a critical 3D computer vision task that partitions point cloud data into semantically meaningful groups (e.g., cars, trees, buildings) or individual objects. By analyzing geometric features (shape, curvature) and semantic attributes (class labels), it enables machines to understand 3D environments. Widely used in autonomous driving (scene perception), robotics (object manipulation), and urban mapping (infrastructure analysis).
