3-D Vehicle Detection Enhancement Using Tracking Feedback in Sparse Point Clouds Environments-Reference-Cited by-同舟云学术

3-D Vehicle Detection Enhancement Using Tracking Feedback in Sparse Point Clouds Environments

Published:2023 Issue: Volume:4 Page:471-480
ISSN:2687-7813
Container-title:IEEE Open Journal of Intelligent Transportation Systems
language:
Short-container-title:IEEE Open J. Intell. Transp. Syst.

Author:

Qian Yeqiang¹^ORCID,Wang Xiaoliang²^ORCID,Zhuang Hanyang³^ORCID,Wang Chunxiang²^ORCID,Yang Ming²^ORCID

Affiliation:

1. Global Institute of Future Technology, Shanghai Jiao Tong University, Shanghai, China

2. Department of Automation, Shanghai Jiao Tong University, Shanghai, China

3. University of Michigan–Shanghai Jiao Tong University Joint Institute, Shanghai Jiao Tong University, Shanghai, China

Funder

National Natural Science Foundation of China

2022 Open Project Program of Guangxi Key Laboratory of Automobile Components and Vehicle Technology

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Science Applications,Mechanical Engineering,Automotive Engineering

Link

http://xplorestaging.ieee.org/ielx7/8784355/9999144/10147030.pdf?arnumber=10147030

Reference37 articles.

1. VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection

2. PointPillars: Fast Encoders for Object Detection From Point Clouds

3. LaserNet: An Efficient Probabilistic 3D Object Detector for Autonomous Driving

4. From points to parts: 3D object detection from point cloud with part-aware and part-aggregation network;shi;IEEE Trans Pattern Anal Mach Intell,2021

5. PointRCNN: 3D Object Proposal Generation and Detection From Point Cloud

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