Abstract
Face-off is an interesting case of style transfer where the facial expressions and attributes of one person could be fully transformed to another face. We are interested in the unsupervised training process which only requires two sequences of unaligned video frames from each person and learns what shared attributes to extract automatically. In this project, we explored various improvements for adversarial training (i.e. CycleGAN[Zhu et al., 2017]) to capture details in facial expressions and head poses and thus generate transformation videos of higher consistency and stability.
Abstract (translated)
对峙是风格转移的一个有趣案例，其中一个人的面部表情和属性可以完全转变为另一个面孔。我们对无监督的训练过程感兴趣，该过程仅需要来自每个人的两个未对齐视频帧序列，并且学习自动提取哪些共享属性。在这个项目中，我们探讨了对抗训练的各种改进（即CycleGAN [Zhu et al。，2017]），以捕捉面部表情和头部姿势的细节，从而生成更高一致性和稳定性的转换视频。
URL
https://arxiv.org/abs/1712.03451
