Deep Tree Learning for Zero-Shot Face Anti-Spoofing

@article{Liu2019DeepTL,
  title={Deep Tree Learning for Zero-Shot Face Anti-Spoofing},
  author={Yaojie Liu and J. Stehouwer and Amin Jourabloo and X. Liu},
  journal={2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2019},
  pages={4675-4684}
}
  • Yaojie Liu, J. Stehouwer, +1 author X. Liu
  • Published 2019
  • Computer Science
  • 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • Face anti-spoofing is designed to keep face recognition systems from recognizing fake faces as the genuine users. [...] Key Method The tree is learned to partition the spoof samples into semantic sub-groups in an unsupervised fashion. When a data sample arrives, being know or unknown attacks, DTN routes it to the most similar spoof cluster, and make the binary decision. In addition, to enable the study of ZSFA, we introduce the first face anti-spoofing database that contains diverse types of spoof attacks…Expand Abstract
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    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 51 REFERENCES
    Context based face anti-spoofing
    118
    Learning Deep Models for Face Anti-Spoofing: Binary or Auxiliary Supervision
    133
    Face anti-spoofing using Haralick features
    36
    On the effectiveness of local binary patterns in face anti-spoofing
    458
    Face De-Spoofing: Anti-Spoofing via Noise Modeling
    75
    A face antispoofing database with diverse attacks
    365
    Face Antispoofing Using Speeded-Up Robust Features and Fisher Vector Encoding
    85
    Face Spoof Detection With Image Distortion Analysis
    349
    An original face anti-spoofing approach using partial convolutional neural network
    98