Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Multi-Expert Adversarial Attack Detection in Person Re-identification
  Using Context Inconsistency   The success of deep neural networks (DNNs) has promoted the widespread
applications of person re-identification (ReID). However, ReID systems inherit
the vulnerability of DNNs to malicious attacks of visually inconspicuous
adversarial perturbations. Detection of adversarial attacks is, therefore, a
fundamental requirement for robust ReID systems. In this work, we propose a
Multi-Expert Adversarial Attack Detection (MEAAD) approach to achieve this goal
by checking context inconsistency, which is suitable for any DNN-based ReID
systems. Specifically, three kinds of context inconsistencies caused by
adversarial attacks are employed to learn a detector for distinguishing the
perturbed examples, i.e., a) the embedding distances between a perturbed query
person image and its top-K retrievals are generally larger than those between a
benign query image and its top-K retrievals, b) the embedding distances among
the top-K retrievals of a perturbed query image are larger than those of a
benign query image, c) the top-K retrievals of a benign query image obtained
with multiple expert ReID models tend to be consistent, which is not preserved
when attacks are present. Extensive experiments on the Market1501 and
DukeMTMC-ReID datasets show that, as the first adversarial attack detection
approach for ReID, MEAAD effectively detects various adversarial attacks and
achieves high ROC-AUC (over 97.5%).

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The categories of this paper are: gr-qc
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The categories of this paper are: nucl-ex
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The categories of this paper are: ao-sci
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The categories of this paper are: comp-gas
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The categories of this paper are: chao-dyn
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The categories of this paper are: hep-ex
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The categories of this paper are: acc-phys
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The categories of this paper are: solv-int
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The categories of this paper are: eess
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The categories of this paper are: chem-ph
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The categories of this paper are: supr-con
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The categories of this paper are: stat
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The categories of this paper are: bayes-an
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The categories of this paper are: mtrl-th
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The categories of this paper are: funct-an
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The categories of this paper are: q-alg