A Systematical Solution for Face De-Identification | |
Yang, Songlin1,2; Wang, Wei1; Cheng, Yuehua2; Dong, Jing1 | |
2021-09 | |
会议名称 | Chinese Conference on Biometric Recognition |
会议日期 | 2021-9 |
会议地点 | Shanghai |
摘要 | With the identity information in face data more closely related to personal credit and property security, people pay increasing at[1]attention to the protection of face data privacy. In different tasks, people have various requirements for face de-identification (De-ID), so we propose a systematical solution compatible for these De-ID operations. Firstly, an attribute disentanglement and generative network is con[1]structed to encode two parts of the face, which are the identity (facial features like mouth, nose and eyes) and expression (including expression, pose and illumination). Through face swapping, we can remove the original ID completely. Secondly, we add an adversarial vector mapping network to perturb the latent code of the face image, different from previous traditional adversarial methods. Through this, we can construct unrestricted adversarial image to decrease ID similarity recognized by model. Our method can flexibly de-identify the face data in various ways and the processed images have high image quality. |
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 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/57547 |
专题 | 模式识别实验室 |
通讯作者 | Wang, Wei |
作者单位 | 1.Institute of Automation, Chinese Academy of Sciences(CASIA) 2.Nanjing University of Aeronautics and Astronautics |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Yang, Songlin,Wang, Wei,Cheng, Yuehua,et al. A Systematical Solution for Face De-Identification[C],2021. |
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文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
A Systematical Solut(3192KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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