PPMGNet: A Neural Network Algorithm for Point Cloud 3D Object Detection

摘要

3D object detection based on point cloud data is an essential part of L4 automatic driving. This paper proposes a novel end-to-end trainable deep learning network structure, PPMGNet, which can quickly encode point clouds, obtain the spatial feature of point clouds, predict multiple categories, and perform 3D object detection in real time. A large number of experiments show that in terms of speed and accuracy, PPMGNet's detection performance is very suitable for direct deployment in autonomous driving applications.