• Corpus ID: 58014139

Enhance the Motion Cues for Face Anti-Spoofing using CNN-LSTM Architecture

@article{Tu2019EnhanceTM,
  title={Enhance the Motion Cues for Face Anti-Spoofing using CNN-LSTM Architecture},
  author={Xiaoguang Tu and Hengsheng Zhang and M. Xie and Yao Luo and Yuefei Zhang and Z. Ma},
  journal={ArXiv},
  year={2019},
  volume={abs/1901.05635}
}
Spatio-temporal information is very important to capture the discriminative cues between genuine and fake faces from video sequences. To explore such a temporal feature, the fine-grained motions (e.g., eye blinking, mouth movements and head swing) across video frames are very critical. In this paper, we propose a joint CNN-LSTM network for face anti-spoofing, focusing on the motion cues across video frames. We first extract the high discriminative features of video frames using the conventional… 

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