Transformer tracking with multi-scale dual-attention

Transformer tracking with multi-scale dual-attention

Abstract Transformer-based trackers greatly improve tracking success rate and precision rate. Attention mechanism in Transformer can fully explore the context information across successive frames. Nevertheless, it ignores the equally important local information and structured spatial information. An...

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Bibliographic Details
Main Authors: Jun Wang, Changwang Lai, Wenshuang Zhang, Yuanyun Wang, Chenchen Meng
Format: Article
Language:English
Published: Springer 2023-04-01
Series:Complex & Intelligent Systems
Subjects:
Transformer
Attention mechanism
Context information
Local information
Feature fusion network
Online Access:https://doi.org/10.1007/s40747-023-01043-1

Internet

https://doi.org/10.1007/s40747-023-01043-1

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