Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 41, 2024 No. 6
1869-1875

Face anti-spoofing method based on content style enhancement and feature embedding optimization

He Dong
Guo Hui
Li Zhendong
Liu Hao
School of Information Engineering, Ningxia University, Yinchuan 750021, China
DOI: 10.19734/j.issn.1001-3695.2023.09.0443

Abstract

In response to the issues of inadequate feature representation in existing face anti-spoofing algorithms and poor cross-dataset generalization performance, this paper proposed a face anti-spoofing method based on content-style enhancement and feature embedding optimization. Firstly, this method utilized a ResNet-18 encoder to extract generic features from multiple source domains, and then subjected to separation through two self-adaptive modules with different attention mechanisms, enhancing the representation of global content features and local style features. Secondly, based on the AdaIN algorithm, it organically fused content features with style features, further improving the feature representation, and the fused features were subsequently input to specific classifiers and domain discriminators for adversarial training. Finally, by employing average negative samples and semi-hard sample triplet mining to optimize feature embeddings, effectively striking a balance between intra-class cohesion and inter-class discrimination, better capturing the boundaries between genuine and spoofed categories. The proposed method was trained and tested on four benchmark datasets, suchas CASIA-FASD, REPLAY-ATTACK, MSU-MFSD, and OULU-NPU. It achieves accuracy of 6.33%, 12.05%, 8.38% and 10.59% respectively, which are superior to existing algorithms. This indicates that the proposed method can significantly improve the generalization performance of face live detection models in cross-dataset testing.

Foundation Support

国家自然科学基金资助项目(62076142)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.09.0443
Publish at: Application Research of Computers Printed Article, Vol. 41, 2024 No. 6
Section: Technology of Graphic & Image
Pages: 1869-1875
Serial Number: 1001-3695(2024)06-039-1869-07

Publish History

[2023-12-19] Accepted Paper
[2024-06-05] Printed Article

Cite This Article

何东, 郭辉, 李振东, 等. 基于内容风格增强和特征嵌入优化的人脸活体检测方法 [J]. 计算机应用研究, 2024, 41 (6): 1869-1875. (He Dong, Guo Hui, Li Zhendong, et al. Face anti-spoofing method based on content style enhancement and feature embedding optimization [J]. Application Research of Computers, 2024, 41 (6): 1869-1875. )

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  • 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.

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