论文标题
探索表达式：使用辅助分类器生成对抗网络的面部表达生成
Explore the Expression: Facial Expression Generation using Auxiliary Classifier Generative Adversarial Network
论文作者
论文摘要
面部表情是一种非语言交流的形式，人类无缝地为有意义的信息传递而无缝地表现。然而，随着生成模型的出现，大多数文献都解决了面部表达识别方面，除了仅仅对一组表达式的分类外，还可以探索影响空间。在本文中，我们提出了一种生成模型体系结构，该体系结构可靠地为多个角色身份生成一组面部表达式，并通过组合简单的形式来探讨生成复杂表达式的可能性。
Facial expressions are a form of non-verbal communication that humans perform seamlessly for meaningful transfer of information. Most of the literature addresses the facial expression recognition aspect however, with the advent of Generative Models, it has become possible to explore the affect space in addition to mere classification of a set of expressions. In this article, we propose a generative model architecture which robustly generates a set of facial expressions for multiple character identities and explores the possibilities of generating complex expressions by combining the simple ones.
