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

Yu Xing

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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Cite: BibTeX Plain Text

@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

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

Abstract

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