May 5, 2022, 1:12 a.m. | Yiming Li, Haoxiang Zhong, Xingjun Ma, Yong Jiang, Shu-Tao Xia

cs.LG updates on arXiv.org arxiv.org

Visual object tracking (VOT) has been widely adopted in mission-critical
applications, such as autonomous driving and intelligent surveillance systems.
In current practice, third-party resources such as datasets, backbone networks,
and training platforms are frequently used to train high-performance VOT
models. Whilst these resources bring certain convenience, they also introduce
new security threats into VOT models. In this paper, we reveal such a threat
where an adversary can easily implant hidden backdoors into VOT models by
tempering with the training process. …

arxiv attacks backdoor cv tracking

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