Multi-Target Multi-Camera Tracking of Vehicles by Graph Auto-Encoder and Self-Supervised Camera Link Model-Reference-Cited by-同舟云学术

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Multi-Target Multi-Camera Tracking of Vehicles by Graph Auto-Encoder and Self-Supervised Camera Link Model

Published:2022-01 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE/CVF Winter Conference on Applications of Computer Vision Workshops (WACVW)
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Author:

Hsu Hung-Min¹,Wang Yizhou¹,Cai Jiarui¹,Hwang Jenq-Neng¹

Affiliation:

1. University of Washington,Seattle,WA,USA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9707470/9707509/09707589.pdf?arnumber=9707589

Reference58 articles.

1. Towards real-time systems for vehicle reidentification, multi-camera tracking, and anomaly detection;peri;Proc of the IEEE Conference on Com puter Vision and Pattern Recognition,2020

2. Single/cross-camera multiple-person tracking by graph matching

3. Spatio-temporal consistency and hierarchical matching for multi-target multi-camera vehicle tracking;li;Proc CVPR Workshops,2019

4. Online-Learning-Based Human Tracking Across Non-Overlapping Cameras

5. Branch-and-price global optimization for multi-view multi-target tracking

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Learning to Track With Dynamic Message Passing Neural Network for Multi-Camera Multi-Object Tracking;IEEE Access;2024

2. Multi-camera multi-object tracking: A review of current trends and future advances;Neurocomputing;2023-10

3. Multi-Object Multi-Camera Tracking Based on Deep Learning for Intelligent Transportation: A Review;Sensors;2023-04-10

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