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MSA-CNN: Face Morphing Detection via a Multiple Scales Attention Convolutional Neural Network

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Digital Forensics and Watermarking (IWDW 2021)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 13180))

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Abstract

Face morphing attack is becoming a serious threat to the existing face recognition systems. Some different approaches for morphing attack detection have been put forward. However, there are few methods concentrated on detecting the morphing artifacts, which often appear in morphed facial images. In this work, we propose a multiple scales attention convolutional neural network (MSA-CNN), a novel approach that can effectively detect the morphing artifacts in face morphing attacks. It utilizes the attention mechanism to continuously pay attention to the morphing artifacts in multiple scales and finally realizes face morphing detection. Experimental results and analysis show that it can effectively locate the region of morphing artifacts, and outperforms the existing deep learning-based blind face morphing detection frameworks.

This research was supported by National Natural Science Foundation of China under grant nos. 62072055 and U1936115. It was also supported by Scientific Research Foundation of Hunan Provincial Education Department under grant nos. 20K098 and 19C1468, and co-funded by Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture under grant no. ZNKZN2019.

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Author information

Authors and Affiliations

  1. Huaihua University, Huaihua, 418000, China

    Le-Bing Zhang & Juan Cai

  2. Hunan University, Changsha, 410082, China

    Fei Peng

  3. Changsha University of Science and Technology, Changsha, 410114, China

    Min Long

Authors
  1. Le-Bing Zhang
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  2. Juan Cai
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  3. Fei Peng
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  4. Min Long
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Corresponding author

Correspondence to Juan Cai .

Editor information

Editors and Affiliations

  1. Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China

    Xianfeng Zhao

  2. University of Florence, Florence, Italy

    Alessandro Piva

  3. Universidade de Vigo, Vigo, Spain

    Pedro Comesaña-Alfaro

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Zhang, LB., Cai, J., Peng, F., Long, M. (2022). MSA-CNN: Face Morphing Detection via a Multiple Scales Attention Convolutional Neural Network. In: Zhao, X., Piva, A., Comesaña-Alfaro, P. (eds) Digital Forensics and Watermarking. IWDW 2021. Lecture Notes in Computer Science(), vol 13180. Springer, Cham. https://doi.org/10.1007/978-3-030-95398-0_2

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  • DOI: https://doi.org/10.1007/978-3-030-95398-0_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-95397-3

  • Online ISBN: 978-3-030-95398-0

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