TFNet: Exploiting Temporal Cues for Fast and Accurate LiDAR Semantic Segmentation

arXiv:2309.07849v3 Announce Type: replace
Abstract: LiDAR semantic segmentation plays a crucial role in enabling autonomous driving and robots to understand their surroundings accurately and robustly. A multitude of methods exist within this domain, including point-based, range-image-based, polar-coordinate-based, and hybrid strategies. Among these, range-image-based techniques have gained widespread adoption in practical applications due to their efficiency. However, they face a significant challenge known as the ``many-to-one'' problem caused by the range image's limited horizontal and vertical angular resolution. As a result, …

abstract adoption arxiv autonomous autonomous driving cs.cv domain driving enabling hybrid image lidar polar robots role segmentation semantic strategies temporal type