Supar Sparse 3D Object Detection | |
Fan L(范略)1,2,5; Yang YX(杨禹雪)1,2,5; Wang F(王峰)3; Wang NY(王乃岩)3; Zhang ZX(张兆翔)1,2,4,5 | |
刊名 | IEEE Transactions on Pattern Analysis and Machine Intelligence
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2023-06-15 | |
卷号 | 45期号:10页码:12490-12505 |
关键词 | 目标检测 点云 自动驾驶 |
DOI | 10.1109/TPAMI.2023.3286409 |
英文摘要 | As the perception range of LiDAR expands, LiDAR-based 3D object detection contributes ever-increasingly to the long-range perception in autonomous driving. Mainstream 3D object detectors often build dense feature maps, where the cost is quadratic to the perception range, making them hardly scale up to the long-range settings. To enable efficient long-range detection, we first propose a fully sparse object detector termed FSD. FSD is built upon the general sparse voxel encoder and a novel sparse instance recognition (SIR) module. SIR groups the points into instances and applies highly-efficient instance-wise feature extraction. The instance-wise grouping sidesteps the issue of the center feature missing, which hinders the design of the fully sparse architecture. To further enjoy the benefit of fully sparse characteristic, we leverage temporal information to remove data redundancy and propose a super sparse detector named FSD++. FSD++ first generates residual points, which indicate the point changes between consecutive frames. The residual points, along with a few previous foreground points, form the super sparse input data, greatly reducing data redundancy and computational overhead. We comprehensively analyze our method on the large-scale Waymo Open Dataset, and state-of-the-art performance is reported. To showcase the superiority of our method in long-range detection, we also conduct experiments on Argoverse 2 Dataset, where the perception range (200m) is much larger than Waymo Open Dataset (75m). |
URL标识 | 查看原文 |
语种 | 英语 |
内容类型 | 期刊论文 |
源URL | [http://ir.ia.ac.cn/handle/173211/57418] ![]() |
专题 | 自动化研究所_智能感知与计算研究中心 |
通讯作者 | Zhang ZX(张兆翔) |
作者单位 | 1.中国科学院大学 2.智能感知与计算研究中心 3.图森未来 4.中国科学院香港创新研究院,人工智能与机器人研究中心 5.中国科学院自动化所 |
推荐引用方式 GB/T 7714 | Fan L,Yang YX,Wang F,et al. Supar Sparse 3D Object Detection[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence,2023,45(10):12490-12505. |
APA | Fan L,Yang YX,Wang F,Wang NY,&Zhang ZX.(2023).Supar Sparse 3D Object Detection.IEEE Transactions on Pattern Analysis and Machine Intelligence,45(10),12490-12505. |
MLA | Fan L,et al."Supar Sparse 3D Object Detection".IEEE Transactions on Pattern Analysis and Machine Intelligence 45.10(2023):12490-12505. |
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