@inproceedings{e0906fa7a2034fddb420756c1bc606cd,
title = "A Decision Fusion Model for 3D Detection of Autonomous Driving",
abstract = "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.",
keywords = "3D car detection, Autonomous driving, decision fusion, network",
author = "Zhen Ye and Jianru Xue and Jianwu Fang and Jian Dou and Yuxin Pan",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 Chinese Automation Congress, CAC 2018 ; Conference date: 30-11-2018 Through 02-12-2018",
year = "2018",
month = jul,
day = "2",
doi = "10.1109/CAC.2018.8623699",
language = "英语",
series = "Proceedings 2018 Chinese Automation Congress, CAC 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "3773--3777",
booktitle = "Proceedings 2018 Chinese Automation Congress, CAC 2018",
}