3D-Aware Adversarial Makeup Generation for Facial Privacy Protection | |
Yueming Lyu![]() ![]() ![]() ![]() ![]() | |
发表期刊 | IEEE Transactions on Pattern Analysis and Machine Intelligence
![]() |
2023 | |
页码 | 16 |
摘要 | 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. |
七大方向——子方向分类 | 图像视频处理与分析 |
国重实验室规划方向分类 | 视觉信息处理 |
是否有论文关联数据集需要存交 | 否 |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/56619 |
专题 | 模式识别实验室 |
通讯作者 | Jing Dong |
作者单位 | 1.Institute of Automation Chinese Academy of Sciences 2.University of Chinese Academy of Sciences |
推荐引用方式 GB/T 7714 | Yueming Lyu,Yue Jiang,Ziwen He,et al. 3D-Aware Adversarial Makeup Generation for Facial Privacy Protection[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence,2023:16. |
APA | Yueming Lyu,Yue Jiang,Ziwen He,Bo Peng,Yunfan Liu,&Jing Dong.(2023).3D-Aware Adversarial Makeup Generation for Facial Privacy Protection.IEEE Transactions on Pattern Analysis and Machine Intelligence,16. |
MLA | Yueming Lyu,et al."3D-Aware Adversarial Makeup Generation for Facial Privacy Protection".IEEE Transactions on Pattern Analysis and Machine Intelligence (2023):16. |
条目包含的文件 | 下载所有文件 | |||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
1_TPAMI.pdf(13973KB) | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论