论文标题
带有连续情感标签的面部表情编辑
Facial Expression Editing with Continuous Emotion Labels
论文作者
论文摘要
最近，深层生成模型在自动面部表达编辑领域取得了令人印象深刻的结果。但是，到目前为止提出的方法假定人类情感的离散表示，因此在非差异情绪表达的建模中受到限制。为了克服这一限制，我们探讨了如何使用连续的情绪表示来控制自动表达式编辑。我们提出了一个深层生成模型，该模型可用于根据连续的二维情感标签在面部图像中操纵面部表情。一个维度代表一种情感的价，另一个代表其唤醒程度。我们通过使用分类器网络进行定量分析以及定性分析来证明模型的功能。
Recently deep generative models have achieved impressive results in the field of automated facial expression editing. However, the approaches presented so far presume a discrete representation of human emotions and are therefore limited in the modelling of non-discrete emotional expressions. To overcome this limitation, we explore how continuous emotion representations can be used to control automated expression editing. We propose a deep generative model that can be used to manipulate facial expressions in facial images according to continuous two-dimensional emotion labels. One dimension represents an emotion's valence, the other represents its degree of arousal. We demonstrate the functionality of our model with a quantitative analysis using classifier networks as well as with a qualitative analysis.
