FRNet: Frustum-Range Networks for Scalable LiDAR Segmentation

arXiv:2312.04484v2 Announce Type: replace
Abstract: LiDAR segmentation has become a crucial component in advanced autonomous driving systems. Recent range-view LiDAR segmentation approaches show promise for real-time processing. However, they inevitably suffer from corrupted contextual information and rely heavily on post-processing techniques for prediction refinement. In this work, we propose FRNet, a simple yet powerful method aimed at restoring the contextual information of range image pixels using corresponding frustum LiDAR points. Firstly, a frustum feature encoder module is used to extract …

arxiv cs.cv cs.ro lidar networks scalable segmentation type