This paper introduces MakeupBag, a novel method for automatic makeup style transfer. Our proposed technique can transfer a new makeup style from a reference face image to another previously unseen facial photograph. We solve makeup disentanglement and facial makeup application as separable objectives, in contrast to other current deep methods that entangle the two tasks. MakeupBag presents a significant advantage for our approach as it allows customization and pixel specific modification of the extracted makeup style, which is not possible using current methods. Extensive experiments, both qualitative and numerical, are conducted demonstrating the high quality and accuracy of the images produced by our method. Furthermore, in contrast to most other current methods, MakeupBag tackles both classical and extreme and costume makeup transfer. In a comparative analysis, MakeupBag is shown to outperform current state-of-the-art approaches.
翻译:本文介绍化妆品Bag, 这是自动化妆风格传输的一种新颖方法。 我们所推荐的技术可以将一个新的化妆品样式从一个参考面容图像转换到另一个先前看不见的面部照片。 我们解决化妆品分解和面部化妆应用作为可分离的目标, 与目前将这两项任务缠绕在一起的其他深层方法不同。 化妆品Bag为我们的方法带来了很大的优势, 因为它允许对提取的化妆品样式进行定制化和像素特定修改, 而使用当前方法是行不通的。 大量定性和数字实验都展示了我们方法产生的图像的高质量和准确性。 此外, 与大多数其他目前的方法不同, 化妆品Bag 处理传统和极端的以及化妆品的转换。 在比较分析中, 化妆品Bag 显示比目前更符合最新工艺的方法。