High-level manipulation of facial expressions in images --- such as changing
a smile to a neutral expression --- is challenging because facial expression
changes are highly non-linear, and vary depending on the appearance of the
face. We present a fully automatic approach to editing faces that combines the
advantages of flow-based face manipulation with the
本文介绍了一种新颖的深度学习方法，用于对 “野外” 视频中演员情绪状态的逼真操作。该方法基于演员输入场景中的参数化 3D 面部表示，并使用新颖的深度域转换框架，结合动态信息，以一致而可信的方式改变面部表情。经过广泛的定性和定量评估和比较，我们的方法证明了其有效性并取得了尤为有前途的结果。该方法可应用于电影后期制作、视频游戏和逼真的情感化头像等各种领域。