论文标题
使用生成的对抗网络，一种无监督的方法来改变人类肤色
An Unsupervised Approach towards Varying Human Skin Tone Using Generative Adversarial Networks
论文作者
论文摘要
随着增强和虚拟现实的日益普及，零售商现在更加专注于客户满意度以增加销售量。尽管增强现实并不是一个新概念，但在过去几年中，它引起了很多需要的关注。我们目前的工作针对这个方向，该方向可用于增强基于现实的各种虚拟和增强现实应用程序中的用户体验。我们建议一个模型来改变一个人的肤色。考虑到一个人或一群具有一定价值的人的输入图像，表明肤色会改变向公平或黑暗的变化，此方法可以改变图像中人的肤色。这是一种无监督的方法，在姿势，照明，图像中的人数等方面也不受限。这项工作的目的是减少使用现有应用程序（例如Photoshop）或新手更改肤色所必需的时间和精力。为了确定这种方法的疗效，我们将我们的结果与一些流行的照片编辑器的结果进行了比较，也将与人类属性操纵有关的一些现有基准方法进行了比较。在不同数据集上进行的严格实验在合成感知令人信服的输出方面显示了该方法的有效性。
With the increasing popularity of augmented and virtual reality, retailers are now focusing more towards customer satisfaction to increase the amount of sales. Although augmented reality is not a new concept but it has gained much needed attention over the past few years. Our present work is targeted towards this direction which may be used to enhance user experience in various virtual and augmented reality based applications. We propose a model to change skin tone of a person. Given any input image of a person or a group of persons with some value indicating the desired change of skin color towards fairness or darkness, this method can change the skin tone of the persons in the image. This is an unsupervised method and also unconstrained in terms of pose, illumination, number of persons in the image etc. The goal of this work is to reduce the time and effort which is generally required for changing the skin tone using existing applications (e.g., Photoshop) by professionals or novice. To establish the efficacy of this method we have compared our result with that of some popular photo editor and also with the result of some existing benchmark method related to human attribute manipulation. Rigorous experiments on different datasets show the effectiveness of this method in terms of synthesizing perceptually convincing outputs.
