mlsanityData to 7 Oct 2026

Deep learning for 3D Object Detection and Tracking in Autonomous Driving: A Brief Survey

arXiv 2311.06043 ↗First posted 10 Nov 2023cs.CV cs.AIcited by 1

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Abstract (arXiv)

Object detection and tracking are vital and fundamental tasks for autonomous driving, aiming at identifying and locating objects from those predefined categories in a scene. 3D point cloud learning has been attracting more and more attention among all other forms of self-driving data. Currently, there are many deep learning methods for 3D object detection. However, the tasks of object detection and tracking for point clouds still need intensive study due to the unique characteristics of point cloud data. To help get a good grasp of the present situation of this research, this paper shows recent advances in deep learning methods for 3D object detection and tracking.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 41 of its 55 references that are in the map. First posted on arXiv 10 Nov 2023.

Builds on

41 of 55 references.

References · 41

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29 more
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