App. Res. of Comp. Accepted Paper
Vol. 41, 2024 No. 8

Face anti-spoofing algorithm based on disentangled representation learning

Zhou Yiyan
Shi Liang
Zhang Ao
Yue Xiaoyu
School of Computer Science, Jiangsu University of Science & Technology, Zhenjiang Jiangsu 212114，China
DOI: 10.19734/j.issn.1001-3695.2023.11.0554

Abstract

To solve the problems of low recognition accuracy and poor generalization performance of existing face anti-spoofing models in different application scenarios, this paper adopts the idea of disentangled representation learning and proposes a face anti-spoofing method based on disentangled representation learning. This method adopts U-Net architecture and ResNet-18 as the encoder-decoder. In the first stage of training, input real samples so that the encoder only learns information related to real samples. In the second stage, this paper builds an adversarial learning network, input samples without labels, feature fusion of the pre-trained encoder output and the new encoder output, reconstruct the image by the decoder, and perform adversarial training with the original image in the discriminator to Achieve feature decoupling. Compared with some classic face anti-spoofing methods, the model in this paper has achieved better detection performance. The lowest detection error rate in several experiments on the OULU-NPU data set is only 0.8%, which is better than classic detection methods such as STDN. The face anti-spoofing method in this article uses staged training to enable the model to obtain a more discriminative feature representation than the end-to-end model in adversarial training. It adopts a multi-classification strategy in the deception feature map output stage to reduce the impact of different image noises on classification results, and experiments on public data sets verified the effectiveness of the algorithm.

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.11.0554
Publish at: Application Research of Computers Accepted Paper, Vol. 41, 2024 No. 8

Publish History

[2024-01-19] Accepted Paper

Cite This Article

周毅岩, 石亮, 张遨, 等. 基于解纠缠表示学习的人脸反欺骗算法实现* [J]. 计算机应用研究, 2024, 41 (8). (2024-04-10). https://doi.org/10.19734/j.issn.1001-3695.2023.11.0554. (Zhou Yiyan, Shi Liang, Zhang Ao, et al. Face anti-spoofing algorithm based on disentangled representation learning [J]. Application Research of Computers, 2024, 41 (8). (2024-04-10). https://doi.org/10.19734/j.issn.1001-3695.2023.11.0554. )

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.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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