3D Semantic Segmentation is a computer vision task that involves the partitioning of a three-dimensional (3D) point cloud or voxel grid into different segments or regions, with each segment assigned a semantic label that represents the category or class of the objects or surfaces within that segment. This task extends the concept of semantic segmentation from two-dimensional (2D) images to 3D space and is particularly important for understanding and interpreting the 3D environment in applications such as robotics, autonomous driving, augmented reality, and urban planning.