Multi Scan Semantic Segmentation

Multi-scan semantic segmentation, also known as 4D LiDAR semantic segmentation, aims to classify each point in a sequence of LiDAR scans, identifying both its semantic category (e.g., car, pedestrian, road) and its dynamic state (moving or stationary). Current research focuses on efficient algorithms, often employing projection-based approaches or iterative refinement of a global point cloud to overcome the computational challenges of processing multiple scans. This technology is crucial for autonomous driving, improving the accuracy of tasks like path planning and object tracking by providing a richer, temporally consistent understanding of the environment.