A Lightweight and Detector-Free 3D Single Object Tracker on Point Clouds-Reference-Cited by-同舟云学术

A Lightweight and Detector-Free 3D Single Object Tracker on Point Clouds

Published:2023-05 Issue:5 Volume:24 Page:5543-5554
ISSN:1524-9050
Container-title:IEEE Transactions on Intelligent Transportation Systems
language:
Short-container-title:IEEE Trans. Intell. Transport. Syst.

Author:

Xia Yan¹^ORCID,Wu Qiangqiang²,Li Wei³^ORCID,Chan Antoni B.²^ORCID,Stilla Uwe¹^ORCID

Affiliation:

1. School of Engineering and Design, Technical University of Munich, Munich, Germany

2. Department of Computer Science, City University of Hong Kong, Kowloon Tong, Hong Kong

3. X-Laboratory, Inceptio Technology (Shanghai) Company Ltd., Shanghai, China

Funder

China Scholarship Council

Research Grants Council of the Hong Kong Special Administrative Region, China

Strategic Research Grant from City University of Hong Kong

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Science Applications,Mechanical Engineering,Automotive Engineering

Link

http://xplorestaging.ieee.org/ielx7/6979/10121021/10050385.pdf?arnumber=10050385

Reference47 articles.

1. SOE-Net: A Self-Attention and Orientation Encoding Network for Point Cloud based Place Recognition

2. Motion Prediction in Visual Object Tracking

3. P2B: Point-to-Box Network for 3D Object Tracking in Point Clouds

4. You don’t only look once: Constructing spatial–temporal memory for integrated 3D object detection and tracking;sun;Proc IEEE/CVF Int Conf Comput Vis (ICCV),2021

5. Box-Aware Feature Enhancement for Single Object Tracking on Point Clouds

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