Computer Science

Computer Science ›› 2023, Vol. 50 ›› Issue (7): 107-118.doi: 10.11896/jsjkx.220700090

• Computer Graphics & Multimedia • Previous Articles     Next Articles

Review of 3D Object Detection for Autonomous Driving

HUO Weile, JING Tao, REN Shuang   

  1. School of Computer and Information Technology,Beijing Jiaotong University,Beijing 100044,China
  • Received:2022-07-11 Revised:2022-11-20 Online:2023-07-15 Published:2023-07-05
  • About author:HUO Weile,born in 1998,postgraduate.Her main research interests include artificial intelligence and virtual reality.REN Shuang,born in 1981,Ph.D,associate professor,Ph.D supervisor,is a member of China Computer Federation.His main research interests include artificial intelligence and virtual reality.
  • Supported by:
    National Natural Science Foundation of China(62072025).

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Abstract: In recent years,with the rapid development of autonomous driving,3D object detection technology as the core of perception systems has received more and more attention and become a hot research direction.At the same time,the wide application of deep learning has made a great breakthrough in 3D object detection technology recently.A large number of excellent algorithms have emerged.This paper systematically summarizes 3D object detection methods for the autonomous driving field and divides the existing algorithms into three categories according to sensor types:image-based 3D object detection,LiDAR-based 3D object detection,and multi-sensor-based 3D object detection.After that,it analyzes the advantages and disadvantages of the three methods in detail.The LiDAR-based 3D object detection algorithms are thoroughly investigated and subdivided.Then it introduces the commonly used 3D object detection datasets in autonomous driving,including KITTI,nuScenes,and Waymo Open Dataset,and compares the performance of the latest 3D object detection algorithms on different datasets.Finally,the future research direction of 3D object detection technology is discussed.

Key words: Autonomous driving, 3D object detection, Deep learning, Point cloud, LiDAR

CLC Number: 

  • TP391.41
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