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- Title
Precision in visual object tracking: a dual-branch approach.
- Authors
Zhou, WenJun; Wang, Nan; Liang, Dong; Peng, Bo
- Abstract
We propose a dual-branch Siamese network for visual object tracking. Our network architecture comprises two distinct branches: a shallow network branch and a deep network branch. The shallow network branch focuses on precise object localization and improving resistance to interference from similar objects. Meanwhile, the deep network branch emphasizes capturing abstract semantic features of the object. To enhance localization accuracy, we integrate a multi-scale KFFM into the shallow network. In addition, we leverage the attention mechanism to further enhance the model's robustness. Through extensive experiments on three publicly available datasets, we demonstrate that our method surpasses state-of-the-art tracking algorithms in terms of performance and accuracy. The source code of this work is available online at https://github.com/mbgzwn/SiamDUL.git.
- Subjects
OBJECT tracking (Computer vision); TRACKING algorithms; SOURCE code
- Publication
Journal of Electronic Imaging, 2024, Vol 33, Issue 2, p23023
- ISSN
1017-9909
- Publication type
Article
- DOI
10.1117/1.JEI.33.2.023023