Security in Transformer Visual Trackers: A Case Study on the Adversarial Robustness of Two Models
Security in Transformer Visual Trackers: A Case Study on the Adversarial Robustness of Two Models
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Author / Creator
Ye, Peng , Chen, Yuanfang , Ma, Sihang , Xue, Feng , Crespi, Noel , Chen, Xiaohan and Fang, Xing
Publisher
Switzerland: MDPI AG
Journal title
Language
English
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Publisher
Switzerland: MDPI AG
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Contents
Visual object tracking is an important technology in camera-based sensor networks, which has a wide range of practicability in auto-drive systems. A transformer is a deep learning model that adopts the mechanism of self-attention, and it differentially weights the significance of each part of the input data. It has been widely applied in the field...
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Full title
Security in Transformer Visual Trackers: A Case Study on the Adversarial Robustness of Two Models
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TN_cdi_doaj_primary_oai_doaj_org_article_d68d7134dd13457c909cfc03b058e119
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_d68d7134dd13457c909cfc03b058e119
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ISSN
1424-8220
E-ISSN
1424-8220
DOI
10.3390/s24144761
