Activity Recognition | Application | Biometrics | Data Imputation | Database | Deep Learning | Expression Recognition | Face Alignment | Face Antispoofing | Face Deidentification | Face Recognition | Face Reconstruction | Forensics | Image Alignment | Image Segmentation | Joint Alignment | Learning | Low-Level Vision | Medical Imaging | Motion Compensation | Multi-Modality | Multimedia Retrieval | Pedestrian Detection | Plant Vision | Semantic Segmentation | Sequence Alignment | Surveillance | Tracking | Typing Behavior

Face Antispoofing

  1. summary image

    Face Anti-spoofing, Face Presentation Attack Detection

    Yaojie Liu, Amin Jourabloo, Yousef Atoum, Xiaoming Liu

    Biometrics utilize physiological, such as fingerprint, face, and iris, or behavioral characteristics, such as typing rhythm and gait, to uniquely identify or authenticate an individual. As biometric systems are widely used in real-world applications including mobile phone authentication and access control, biometric spoof, or Presentation Attack (PA) are becoming a ...

    Continue reading

    Keywords: Face antispoofing

2017

  • Face Anti-Spoofing Using Patch and Depth-based CNNs
    Yousef Atoum, Yaojie Liu, Amin Jourabloo, Xiaoming Liu
    In Proceeding of International Joint Conference on Biometrics (IJCB 2017), Denver, CO, Oct. 2017
    Bibtex | PDF | Project Webpage
  • @inproceedings{ face-anti-spoofing-using-patch-and-depth-based-cnns,
      author = { Yousef Atoum and Yaojie Liu and Amin Jourabloo and Xiaoming Liu },
      title = { Face Anti-Spoofing Using Patch and Depth-based CNNs },
      booktitle = { In Proceeding of International Joint Conference on Biometrics },
      address = { Denver, CO },
      month = { October },
      year = { 2017 },
    }