arXiv:2104.03510

SiamReID: Confuser Aware Siamese Tracker with Re-identification Feature

Abu Md Niamul Taufique, Andreas Savakis, Michael Braun, Daniel Kubacki, Ethan Dell, Lei Qian, Sean M. O'Rourke

제출 2021-04-08

원문 초록

Siamese deep-network trackers have received significant attention in recent years due to their real-time speed and state-of-the-art performance. However, Siamese trackers suffer from similar looking confusers, that are prevalent in aerial imagery and create challenging conditions due to prolonged occlusions where the tracker object re-appears under different pose and illumination. Our work proposes SiamReID, a novel re-identification framework for Siamese trackers, that incorporates confuser rejection during prolonged occlusions and is well-suited for aerial tracking. The re-identification feature is trained using both triplet loss and a class balanced loss. Our approach achieves state-of-the-art performance in the UAVDT single object tracking benchmark.

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