3D-Aware Adversarial Makeup Generation for Facial Privacy Protection

• URL: http://arxiv.org/abs/2306.14640v1
• Date: Mon, 26 Jun 2023 12:27:59 GMT
• Title: 3D-Aware Adversarial Makeup Generation for Facial Privacy Protection
• Authors: Yueming Lyu and Yue Jiang and Ziwen He and Bo Peng and Yunfan Liu and Jing Dong
• Abstract summary: 3D-Aware Adversarial Makeup Generation GAN (3DAM-GAN) A UV-based generator consisting of a novel Makeup Adjustment Module (MAM) and Makeup Transfer Module (MTM) is designed to render realistic and robust makeup. Experiment results on several benchmark datasets demonstrate that 3DAM-GAN could effectively protect faces against various FR models.
• Score: 23.915259014651337
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The privacy and security of face data on social media are facing unprecedented challenges as it is vulnerable to unauthorized access and identification. A common practice for solving this problem is to modify the original data so that it could be protected from being recognized by malicious face recognition (FR) systems. However, such ``adversarial examples'' obtained by existing methods usually suffer from low transferability and poor image quality, which severely limits the application of these methods in real-world scenarios. In this paper, we propose a 3D-Aware Adversarial Makeup Generation GAN (3DAM-GAN). which aims to improve the quality and transferability of synthetic makeup for identity information concealing. Specifically, a UV-based generator consisting of a novel Makeup Adjustment Module (MAM) and Makeup Transfer Module (MTM) is designed to render realistic and robust makeup with the aid of symmetric characteristics of human faces. Moreover, a makeup attack mechanism with an ensemble training strategy is proposed to boost the transferability of black-box models. Extensive experiment results on several benchmark datasets demonstrate that 3DAM-GAN could effectively protect faces against various FR models, including both publicly available state-of-the-art models and commercial face verification APIs, such as Face++, Baidu and Aliyun.

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