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Proceedings of the 2nd International Conference on Machine Learning and Automation, CONF-MLA 2024, November 21, 2024, Adana, Turkey

Research Article

Impact of Resolution and Resize Process on Face Recognition Accuracy with GAN-Generated Images

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  • @INPROCEEDINGS{10.4108/eai.21-11-2024.2354613,
        author={Yu  Xing},
        title={Impact of Resolution and Resize Process on Face Recognition Accuracy with GAN-Generated Images},
        proceedings={Proceedings of the 2nd International Conference on Machine Learning and Automation, CONF-MLA 2024, November 21, 2024, Adana, Turkey},
        publisher={EAI},
        proceedings_a={CONF-MLA},
        year={2025},
        month={3},
        keywords={generative adversarial networks facenet image post-processing},
        doi={10.4108/eai.21-11-2024.2354613}
    }
    
  • Yu Xing
    Year: 2025
    Impact of Resolution and Resize Process on Face Recognition Accuracy with GAN-Generated Images
    CONF-MLA
    EAI
    DOI: 10.4108/eai.21-11-2024.2354613
Yu Xing1,*
  • 1: Xidian University
*Contact email: 21022100042@stu.xidian.edu.cn

Abstract

This paper discusses the challenges facial recognition systems face in recognizing images generated by generative adversarial networks (GANs) and then proposes solutions by simple image processing methods. The study highlights that facial recognition models behave completely differently when dealing with low-resolution, super-resolution, or resized facial images and that the resizing method specifically affects the success rate of GANs. Changing the resolution also seems to affect the attack's success rate slightly.

Keywords
generative adversarial networks facenet image post-processing
Published
2025-03-11
Publisher
EAI
http://dx.doi.org/10.4108/eai.21-11-2024.2354613
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