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June 1, 2021

Improving Transferability of Adversarial Patches on Face Recognition with Generative Models

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Authors

ZXZihao XiaoJohns Hopkins UniversityXGXianfeng GaoFujian Electric Power Survey & Design InstituteCFChilin FuZhejiang Energy Group (China)

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Cite This Study

Xiao et al. (2021) studied this question.

synapsesocial.com/papers/6a0fc4ae9e54838161fd2a74https://doi.org/10.1109/cvpr46437.2021.01167
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Also Consider

Synapse has enriched 3 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Evading Defenses to Transferable Adversarial Examples by Translation-Invariant Attacks2019 · 974 citations
  2. 2Efficient Decision-Based Black-Box Adversarial Attacks on Face Recognition2019 · 406 citations
  3. 3Explaining and Harnessing Adversarial Examples2014 · 8,034 citations