Computer Science

Computer Science ›› 2021, Vol. 48 ›› Issue (4): 316-324.doi: 10.11896/jsjkx.200300128

• Information Security • Previous Articles     Next Articles

Attention-based Hot Block and Saliency Pixel Convolutional Neural Network Method for Face Anti-spoofing

WU Xiao-li, HU Wei   

  1. College of Information Science and Technology,Beijing University of Chemical Technology,Beijing 100029,China
  • Received:2020-06-24 Online:2021-04-15 Published:2021-04-09
  • About author:WU Xiao-li,born in 1995,postgraduate.Her main research interests include face anti-spoofing and deep learning.(xlwu@mail.buct.edu.cn)
    HU Wei,born in 1979,Ph.D,associate professor.His main research interests include face recognition,real-time global illumination rendering,image editing,image recognition and multiple-projector based tiled display.

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Abstract: Face anti-spoofing is used to verify whether the testee is a real person.The diversity of attack methods and the application of face recognition on various embedded and mobile devices with low computing capabilities have made face anti-spoofing a very challenging task.Aiming at face anti-spoofing,an attention-based hot block and saliency pixel convolutional neural network method is proposed.The hot block method replaces the discrimination of the entire face with the determination of 5 hot blocks,which not only reduces the amount of calculation,but also forces the network to focus on hot spots with more discerning information,so as to improve the accuracy of the network.On the other hand,the saliency pixel method performs saliency pixel prediction on the input face image to determine whether the saliency prediction map meets depth characteristics of the face to identify the liveness and the attack.This method fuses the results of hot blocks and saliency pixels to give full play to the role of local features and global features,and further enhances the effect of face anti-spoofing.Compared with existing methods,the proposed method has achieved good results on CASIA-MFSD,Replay-Attack and SiW datasets.

Key words: Attention mechanism, Convolutional neural network, Face anti-spoofing, Hot block, Liveness detection, Saliency pixel

CLC Number: 

  • TP183
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