A Decision Fusion Model for 3D Detection of Autonomous Driving

摘要

This paper proposes a multimodal fusion model for 3D car detection inputting both point clouds and RGB images and generates the corresponding 3D bounding boxes. Our model is composed of two subnetworks: one is point-based method and another is multi-view based method, which is then combined by a decision fusion model. This decision model can absorb the advantages of these two sub-networks and restrict their shortcomings effectively. Experiments on the KITTI 3D car detection benchmark show that our work can achieve state of the art performance.