一个语义讲话风格空间,用于语音驱动的面部动画.
IEEE transactions on visualization and computer graphics
|September 29, 2025
概括
我们为3D面部动画开发了一种新的隐性说话风格空间,自动分离语音风格属性而无需标签. 这使得在语音驱动动画中可以直观地控制面部表情.
科学领域:
- 计算机视觉 计算机视觉
- 计算机图形 计算机图形
- 机器学习 机器学习
背景情况:
- 语音驱动的3D面部动画需要解开身份,语音内容和说话风格.
- 现有的方法通常需要标记数据或缺乏对面部风格的直观控制.
研究的目的:
- 为了引入一个潜在的说话风格空间与语义含义的语音驱动的3D面部动画.
- 为了实现自动分离和直观控制说话风格,而无需手动标签.
主要方法:
- 使用自我监督范式,从3D语音面部动画中学习潜在的风格空间.
- 提出了一种涉及两个深度神经网络的两阶段方法,以分离身份,语音内容和说话风格.
- 培训是在一个新的数据集上进行的,3D说话的面孔具有不同的风格.
主要成果:
- 学习的风格空间自动分离高层属性,如口腔形状和眉毛运动.
- 隐形风格代码的不同通道对应于不同的语义含义.
- 风格空间允许在3D面部动画中直观而灵活地控制说话风格.
结论:
- 拟议的潜在的说话风格空间有效地解开了面部动画的语义属性.
- 这种方法为现实和可控的语音驱动的3D面部动画提供了一个强大的工具.
- 该方法通过实现风格控制而无需明确的风格标签来推进该领域.
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