PANet: LiDAR Panoptic Segmentation with Sparse Instance Proposal and Aggregation
Jianbiao Mei,Yu Yang,Mengmeng Wang,Xiaojun Hou,Laijian Li,Yong Liu,Jianbiao Mei,Yu Yang,Mengmeng Wang,Xiaojun Hou,Laijian Li,Yong Liu
Reliable LiDAR panoptic segmentation (LPS), including both semantic and instance segmentation, is vital for many robotic applications, such as autonomous driving. This work proposes a new LPS framework named PANet to eliminate the dependency on the offset branch and improve the performance on large objects, which are always over-segmented by clustering algorithms. Firstly, we propose a non-learnin...
