Knowledge Commons of Institute of Automation,CAS
Comparison of 3D Object Detection Based on LiDAR Point Cloud | |
Li, Haoran1,2; Zhou, Xiaolei3; Chen, Yaran1,2; Zhang, Qichao1,2; Zhao, Dongbin1,2; Qian, Dianwei3 | |
2019-11 | |
会议名称 | Data Driven Control and Learning Systems Conference (DDCLS) |
会议日期 | 2019-5-24 |
会议地点 | Dali, China |
出版者 | IEEE |
摘要 | 3D object detection and scene understanding are the key technologies for autonomous driving scenarios. Due to the differences in configuration and datasets used by each 3D object detection algorithm, it is difficult to evaluate the performance of each method. In this work, we provide a comparison of the advanced 3D object detection networks based on LiDAR point cloud in recent two years and analyze each network structure in detail. For the open-sourced networks, we reproduce them on KITTI dataset benchmark with following their original algorithms. Meanwhile, in order to provide more powerful results, we also utilize nuScenes dataset to retrain the networks as mentioned above. The experimental results show that the performance of the networks with point cloud and images as input is better than that of a single input network. |
收录类别 | EI |
语种 | 英语 |
七大方向——子方向分类 | 强化与进化学习 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/40310 |
专题 | 多模态人工智能系统全国重点实验室_深度强化学习 |
作者单位 | 1.Institute of Automation, Chinese Academy of Sciences 2.University of Chinese Academy of Sciences 3.School of Control and Computer Engineering, North China Electric Power University |
第一作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Li, Haoran,Zhou, Xiaolei,Chen, Yaran,et al. Comparison of 3D Object Detection Based on LiDAR Point Cloud[C]:IEEE,2019. |
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文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
08908931.pdf(296KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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