CausTrack: Visual tracking via structural causality and deconfounded feature learning

Yongjun Wang

doi:10.1016/j.neucom.2025.132340

2025-12-08

PRE

Yongjun Wang *

Xiaohui Hao

DOI：10.1016/j.neucom.2025.132340

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摘要

En 中文

• 我们提出CausTrack，一种基于因果关系的Transformer，用于鲁棒且可解释的视觉跟踪。 • 我们设计了三个模块，用于因果时序建模、消解特征和可靠估计。 • CausTrack在七个基准测试上达到当前最佳性能，在V100 GPU上运行速度为28 FPS。

期刊

Neurocomputing

IF:

6.5

论文数:

2.5W

被引数:

6.5W

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暂无机构信息

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