论文标题
可逆面具网络面对隐私权
Invertible Mask Network for Face Privacy-Preserving
论文作者
论文摘要
脸部保护是巨大的研究兴趣的热点之一。但是，现有的面部保护方法旨在导致面部缺少语义信息，并且不能保留原始面部信息的可重复性。为了达到处理后的面部的自然性和原始受保护面的可回收性，本文提出了基于可逆“掩码”网络（IMN）的面部保护方法。在IMN中，我们首先引入了一个口罩网，以生成“面具”的脸部。然后，将“面具”的脸放在受保护的脸上，并产生蒙面的脸，其中蒙面的脸与“面具”的脸没有区别。最后，“面具”的脸可以从蒙面的脸部伸出，并向授权用户获取回收的面部，其中恢复的面部与受保护的面孔在视觉上是无法区分的。实验结果表明，所提出的方法不仅可以有效保护受保护的面部的隐私，而且几乎可以从蒙面的脸部完美地恢复受保护的面孔。
Face privacy-preserving is one of the hotspots that arises dramatic interests of research. However, the existing face privacy-preserving methods aim at causing the missing of semantic information of face and cannot preserve the reusability of original facial information. To achieve the naturalness of the processed face and the recoverability of the original protected face, this paper proposes face privacy-preserving method based on Invertible "Mask" Network (IMN). In IMN, we introduce a Mask-net to generate "Mask" face firstly. Then, put the "Mask" face onto the protected face and generate the masked face, in which the masked face is indistinguishable from "Mask" face. Finally, "Mask" face can be put off from the masked face and obtain the recovered face to the authorized users, in which the recovered face is visually indistinguishable from the protected face. The experimental results show that the proposed method can not only effectively protect the privacy of the protected face, but also almost perfectly recover the protected face from the masked face.
