Face Image Reconstruction from Deep Templates

@article{Mai2017FaceIR,
  title={Face Image Reconstruction from Deep Templates},
  author={Guangcan Mai and Kai Cao and Pong Chi Yuen and Anil K. Jain},
  journal={ArXiv},
  year={2017},
  volume={abs/1703.00832}
}
State-of-the-art face recognition systems are based on deep (convolutional) neural networks. [] Key Method Each D-CNN was trained on a different dataset (VGG-Face, CASIA-Webface, or Multi-PIE). The type-I attack achieved a true accept rate (TAR) of 85.48% at a false accept rate (FAR) of 0.1% on the LFW dataset. The corresponding TAR for the type-II attack is 14.71%. Our experimental results demonstrate the need to secure deep templates in face recognition systems.

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