How can one visually characterize people in a decade? In this work, we assemble the Faces Through Time dataset, which contains over a thousand portrait images from each decade, spanning the 1880s to the present day. Using our new dataset, we present a framework for resynthesizing portrait images across time, imagining how a portrait taken during a particular decade might have looked like, had it been taken in other decades. Our framework optimizes a family of per-decade generators that reveal subtle changes that differentiate decade--such as different hairstyles or makeup--while maintaining the identity of the input portrait. Experiments show that our method is more effective in resynthesizing portraits across time compared to state-of-the-art image-to-image translation methods, as well as attribute-based and language-guided portrait editing models. Our code and data will be available at https://facesthroughtime.github.io
翻译:如何在十年内对人进行视觉描述? 在这项工作中,我们汇集了“通过时间穿面”数据集,该数据集包含从1880年代到今天的每十年一千多张肖像图像,覆盖了1880年代到今天。利用我们的新数据集,我们提出了一个框架,用于对不同时间的肖像图像进行重新合成,想象如果在其他几十年中拍摄过,在特定十年中拍摄的肖像会是怎样的。我们的框架优化了每十年生成一个显示细微变化的组合,这些变化会区分十年,例如不同的发型或化妆,同时保持输入肖像的身份。实验显示,我们的方法比最先进的图像到图像的翻译方法更为有效,以及基于属性和语言的肖像编辑模型。我们的代码和数据将在 https://facesovertime.githubio 上提供。