Jointing Recurrent Across-Channel and Spatial Attention for Multi-Object Tracking With Block-Erasing Data Augmentation-Reference-Cited by-同舟云学术

Jointing Recurrent Across-Channel and Spatial Attention for Multi-Object Tracking With Block-Erasing Data Augmentation

Published:2023-08 Issue:8 Volume:33 Page:4054-4069
ISSN:1051-8215
Container-title:IEEE Transactions on Circuits and Systems for Video Technology
language:
Short-container-title:IEEE Trans. Circuits Syst. Video Technol.

Author:

Deng Keyu¹,Zhang Congxuan²^ORCID,Chen Zhen²^ORCID,Hu Weiming³^ORCID,Li Bing³^ORCID,Lu Feng²

Affiliation:

1. School of Measuring and Optical Engineering, Nanchang Hangkong University, Nanchang, China

2. Key Laboratory of Nondestructive Testing, Ministry of Education, School of Measuring and Optical Engineering, Nanchang Hangkong University, Nanchang, China

3. Institute of Automation, Chinese Academy of Sciences, Beijing, China

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

National Natural Science Foundation of Jiangxi Province

Technology Innovation Guidance Program of Jiangxi Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Media Technology

Link

http://xplorestaging.ieee.org/ielx7/76/10207864/10024400.pdf?arnumber=10024400

Reference69 articles.

1. Recurrent Autoregressive Networks for Online Multi-object Tracking

2. Semantic-Aware Occlusion-Robust Network for Occluded Person Re-Identification

3. Simple online and realtime tracking with a deep association metric

4. Multi-target tracking using CNN-based features: CNNMTT

5. SiamFPN: A Deep Learning Method for Accurate and Real-Time Maritime Ship Tracking

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