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This document introduces a new multi-modal visual tracking task called UAV-Anti-UAV, which involves a pursuing UAV tracking a target UAV in a video stream, addressing a gap in current Anti-UAV research. A million-scale dataset of 1,810 annotated videos is constructed to facilitate this research, along with a proposed baseline method called MambaSTS that integrates spatial-temporal-semantic learning. The study highlights significant performance gaps in existing tracking algorithms, indicating the need for fu

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526856790

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EN