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DTFA-Net: Dynamic and Texture Features Fusion Attention Network for Face Antispoofing
Joint Authors
Zhou, Jingmei
Chang, Hui
Cheng, Xin
Wang, Hongfei
Jia, Yilin
Zhao, Xiangmo
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-07-10
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
For face recognition systems, liveness detection can effectively avoid illegal fraud and improve the safety of face recognition systems.
Common face attacks include photo printing and video replay attacks.
This paper studied the differences between photos, videos, and real faces in static texture and motion information and proposed a living detection structure based on feature fusion and attention mechanism, Dynamic and Texture Fusion Attention Network (DTFA-Net).
We proposed a dynamic information fusion structure of an interchannel attention block to fuse the magnitude and direction of optical flow to extract facial motion features.
In addition, for the face detection failure of HOG algorithm under complex illumination, we proposed an improved Gamma image preprocessing algorithm, which effectively improved the face detection ability.
We conducted experiments on the CASIA-MFSD and Replay Attack Databases.
According to experiments, the DTFA-Net proposed in this paper achieved 6.9% EER on CASIA and 2.2% HTER on Replay Attack that was comparable to other methods.
American Psychological Association (APA)
Cheng, Xin& Wang, Hongfei& Zhou, Jingmei& Chang, Hui& Zhao, Xiangmo& Jia, Yilin. 2020. DTFA-Net: Dynamic and Texture Features Fusion Attention Network for Face Antispoofing. Complexity،Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1142574
Modern Language Association (MLA)
Cheng, Xin…[et al.]. DTFA-Net: Dynamic and Texture Features Fusion Attention Network for Face Antispoofing. Complexity No. 2020 (2020), pp.1-11.
https://search.emarefa.net/detail/BIM-1142574
American Medical Association (AMA)
Cheng, Xin& Wang, Hongfei& Zhou, Jingmei& Chang, Hui& Zhao, Xiangmo& Jia, Yilin. DTFA-Net: Dynamic and Texture Features Fusion Attention Network for Face Antispoofing. Complexity. 2020. Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1142574
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1142574