High-efficiency point cloud 3D object detection operated on embedded systems is important for many robotics applications including autonomous driving. Most previous works try to solve it using anchor-based detection methods which come with two drawbacks: post-processing is relatively complex and computationally expensive; tuning anchor parameters is tricky. We are the first to address these drawbacks with an anchor free and Non-Maximum Suppression free one stage detector called AFDet. The entire AFDet can be processed efficiently on a CNN accelerator or a GPU with the simplified post-processing. Without bells and whistles, our proposed AFDet performs competitively with other one stage anchor-based methods on KITTI validation set and Waymo Open Dataset validation set.
@article{arxiv.2006.12671,
title = {AFDet: Anchor Free One Stage 3D Object Detection},
author = {Runzhou Ge and Zhuangzhuang Ding and Yihan Hu and Yu Wang and Sijia Chen and Li Huang and Yuan Li},
journal= {arXiv preprint arXiv:2006.12671},
year = {2020}
}
Comments
Accepted on May 6th, 2020 by CVPRW 2020, published on June 7th, 2020; Baseline detector for the 1st place solutions of Waymo Open Dataset Challenges 2020