Gradually Spatio-Temporal Feature Activation for Target Tracking-Reference-Cited by-同舟云学术

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Gradually Spatio-Temporal Feature Activation for Target Tracking

Published:2024-04-14 Issue: Volume: Page:3925-3929
ISSN:
Container-title:ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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Author:

Deng Yanfang¹,Zhang Canlong¹,Li Zhixin¹,Wei Chunrong²,Wang Zhiwen³,Pan Shuqi¹

Affiliation:

1. Guangxi Normal University,Key Lab of Education Blockchain and Intelligent Technology,Ministry of Education,Guilin,China

2. Guangxi Normal University,Guangxi Key Lab of Multi-Source Information Mining & Security,Guilin,China,541004

3. Guangxi University of Science and Technology,School of Computer Science and Technology,Liuzhou,China,545006

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10445798/10445803/10447555.pdf?arnumber=10447555

Reference20 articles.

1. A survey of appearance models in visual object tracking

2. Staple: Complementary Learners for Real-Time Tracking

3. Siamese Cascaded Region Proposal Networks for Real-Time Visual Tracking

4. Joint compressive representation for multi-feature tracking

5. Deep mutual learning for visual object tracking

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