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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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-05-01
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| Series: | Sensors |
| Subjects: | |
| 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. |
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| ISSN: | 1424-8220 |