Real-Time Monocular Joint Perception Network for Autonomous Driving-Reference-Cited by-同舟云学术

Real-Time Monocular Joint Perception Network for Autonomous Driving

Published:2022-09 Issue:9 Volume:23 Page:15864-15877
ISSN:1524-9050
Container-title:IEEE Transactions on Intelligent Transportation Systems
language:
Short-container-title:IEEE Trans. Intell. Transport. Syst.

Author:

Li Keqiang¹^ORCID,Xiong Hui¹^ORCID,Liu Jinxin¹^ORCID,Xu Qing¹,Wang Jianqiang¹^ORCID

Affiliation:

1. State Key Laboratory of Automotive Safety and Energy, School of Vehicle and Mobility, Tsinghua University, Beijing, China

Funder

National Natural Science Foundation of China

Tsinghua University-Didi Joint Research Center for Future Mobility and Tsinghua University-Huawei Joint Research Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Science Applications,Mechanical Engineering,Automotive Engineering

Link

http://xplorestaging.ieee.org/ielx7/6979/9893028/09705204.pdf?arnumber=9705204

Reference55 articles.

1. CentripetalNet: Pursuing High-Quality Keypoint Pairs for Object Detection

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4. YOLOv4: Optimal speed and accuracy of object detection;bochkovskiy;arXiv 2004 10934,2020

5. ECFFNet: Effective and consistent feature fusion network for RGB-T salient object detection;zhou;IEEE Trans Circuits Syst Video Technol,2021

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