@inproceedings{fc11d686a61c4c91958a5b62c6a5e5f2,
title = "FA3D: Fast and Accurate 3D Object Detection",
abstract = "Fast and accurate detection of objects, in 3D, is one of the critical components in an advanced driver assistance system. In this paper, we aim to develop an accurate 3D object detector that runs in near real-time on low-end embedded systems. We propose an efficient framework that converts raw point cloud into a 3D occupancy cuboid and detects cars using a deep convolutional neural network. Even though the complexity of our proposed model is high, it runs at 7.27 FPS on a Jetson Xavier and at 57.83 FPS on a high-end workstation that is 18 % and 43 % faster than the fastest published method while having a comparable performance with state-of-the-art models on the KITTI dataset. We conduct a comprehensive error analysis on our model and show that two quantities are the principal sources of error among nine predicted attributes. Our source code is available at https://github.com/Selameab/FA3D. {\textcopyright} 2020, Springer Nature Switzerland AG.",
keywords = "3D object detection, Deep neural networks, Smart and autonomous vehicles",
author = "{Habibi Aghdam}, Hamed and Selameab Demilew and Robert Lagani{\'e}re and Emil Petriu",
year = "2020",
month = dec,
day = "7",
doi = "10.1007/978-3-030-64556-4_31",
language = "English",
isbn = "9783030645557",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "397--409",
editor = "George Bebis and Zhaozheng Yin and Edward Kim and Jan Bender and Kartic Subr and Kwon, {Bum Chul} and Jian Zhao and Denis Kalkofen and George Baciu",
booktitle = "Advances in Visual Computing - 15th International Symposium, ISVC 2020, Proceedings",
note = "15th International Symposium on Visual Computing : ISVC 2020 ; Conference date: 05-10-2020 Through 07-10-2020",
}