A Target Tracking Method Based on a Pyramid Channel Attention Mechanism

To enhance the tracking performance of transformer-based trackers in complex scenes, we propose a novel visual object tracking method that incorporates three key components: a pyramid channel attention mechanism, a hierarchical cross-attention structure, and an attention-guided multi-layer perceptro...

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Bibliographic Details
Main Authors: Dongxuan Zhao, Yunsong Li, Jiaxing Li, Xiping Duan, Ning Ma, Yuhe Wang
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Sensors
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Online Access:https://www.mdpi.com/1424-8220/25/10/3214
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Summary:To enhance the tracking performance of transformer-based trackers in complex scenes, we propose a novel visual object tracking method that incorporates three key components: a pyramid channel attention mechanism, a hierarchical cross-attention structure, and an attention-guided multi-layer perceptron. The pyramid channel attention mechanism dynamically enhances informative feature channels across different scales, while the hierarchical cross-attention structure facilitates effective feature interaction. The attention-guided multi-layer perceptron introduces nonlinear transformations under attention guidance to improve feature representation. Experimental results on benchmark datasets demonstrate the superior performance of the proposed method.
ISSN:1424-8220