Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 39, 2022 No. 8
2538-2544

Face anti-spoofing method based on conditional adversarial domain generalization

Cai Tijian
Chen Fuchun
Liu Wenxin
School of Information Engineering, East China Jiaotong University, Nanchang 330013, China
DOI: 10.19734/j.issn.1001-3695.2021.12.0685

Abstract

Aiming at the problems of poor generalization performance and overlapping between classes of existing cross scene face anti-spoofing detection models, this paper proposed a face anti-spoofing method based on conditional adversarial domain generalization. Firstly, the method used U-Net embedded with attention mechanism and ResNet-18 encoder to extract features from multiple source domains, then sent the extracted features to auxiliary classifier, and combined the output of the feature encoder with the prediction results of the classifier by the method of multilinear mapping, and then input into the domain discriminator for adversarial training to achieve feature and class-level alignment of multiple source domains. Secondly, in order to reduce the impact of difficult to transfer samples with inaccurate prediction on domain generalization, this paper used entropy function to control the priority of samples to improve the performance of domain generalization. In addition, by adding a face depth map to further capture the distinguishing features of the real and attack face, and using asymmetric triplet loss constraint as auxiliary supervision to further improve the intra-class compactness and inter-class discrimination. Comparative experiments on public live detection datasets verify the effectiveness of the proposed method.

Foundation Support

国家自然科学基金资助项目(62166018)
江西省重点研发计划资助项目(20203BBE53029)
江西省高等学校教学改革重点研究课题(JXJG-20-5-6)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2021.12.0685
Publish at: Application Research of Computers Printed Article, Vol. 39, 2022 No. 8
Section: Technology of Graphic & Image
Pages: 2538-2544
Serial Number: 1001-3695(2022)08-052-2538-07

Publish History

[2022-03-09] Accepted Paper
[2022-08-05] Printed Article

Cite This Article

蔡体健, 尘福春, 刘文鑫. 基于条件对抗域泛化的人脸活体检测方法 [J]. 计算机应用研究, 2022, 39 (8): 2538-2544. (Cai Tijian, Chen Fuchun, Liu Wenxin. Face anti-spoofing method based on conditional adversarial domain generalization [J]. Application Research of Computers, 2022, 39 (8): 2538-2544. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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