LSK3DNet: Towards Effective and Efficient 3D Perception with Large Sparse Kernels

arXiv:2403.15173v1 Announce Type: new
Abstract: Autonomous systems need to process large-scale, sparse, and irregular point clouds with limited compute resources. Consequently, it is essential to develop LiDAR perception methods that are both efficient and effective. Although naively enlarging 3D kernel size can enhance performance, it will also lead to a cubically-increasing overhead. Therefore, it is crucial to develop streamlined 3D large kernel designs that eliminate redundant weights and work effectively with larger kernels. In this paper, we propose an efficient …

abstract arxiv autonomous autonomous systems compute cs.cv kernel lidar perception performance process resources scale systems type will