Are facial attributes adversarially robust?

  title={Are facial attributes adversarially robust?},
  author={Andras Rozsa and M. G{\"u}nther and Ethan M. Rudd and T. Boult},
  journal={2016 23rd International Conference on Pattern Recognition (ICPR)},
  • Andras Rozsa, M. Günther, +1 author T. Boult
  • Published 2016
  • Computer Science
  • 2016 23rd International Conference on Pattern Recognition (ICPR)
  • Facial attributes are emerging soft biometrics that have the potential to reject non-matches, for example, based on mismatching gender. To be usable in stand-alone systems, facial attributes must be extracted from images automatically and reliably. In this paper, we propose a simple yet effective solution for automatic facial attribute extraction by training a deep convolutional neural network (DCNN) for each facial attribute separately, without using any pre-training or dataset augmentation… CONTINUE READING
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