StyleTalk++:一个统一的框架来控制说话头的说话风格
IEEE transactions on pattern analysis and machine intelligence
|January 24, 2024
概括
这项研究引入了一种新的一次性说话面孔生成方法,该方法捕捉了来自参考视频的独特说话风格. 这种方法可以实现个性化,多样化的说话头视频,由音频和风格代码驱动.
科学领域:
- 计算机视觉 计算机视觉
- 人工智能的人工智能
- 计算机图形 计算机图形
背景情况:
- 个性化的说话风格包括独特的面部表情和头部姿势.
- 现有的一拍式说话面孔方法缺乏捕捉和复制这些个性化的说话风格的能力,导致生成视频的多样性有限.
研究的目的:
- 提出一种一次性,风格可控的说话面孔生成方法.
- 通过从参考视频中提取它们并将它们应用于具有新音频输入的目标肖像中,使各种说话风格的合成成为可能.
主要方法:
- 一个统一的框架为3D形态模型 (3DMM) 合成了风格可控制的系数.
- 风格编码器从参考视频中提取说话风格,将其转化为风格代码.
- 风格感知解码器通过使用双分支架构从音频和风格代码中合成3DMM系数 (面部表情和头部运动).
- 一个图像染器生成最终的说话头视频.
主要成果:
- 该方法成功地产生了视觉上真实的说话头部视频.
- 产生的视频展示了多样化和个性化的说话风格.
- 这种方法只需要一个肖像图像和一个音频剪辑来生成.
结论:
- 提出的方法有效地解决了现有方法在捕捉个性化的说话风格方面的局限性.
- 它提供了一个强大的解决方案,用于生成多样化,风格可控的说话面孔视频.
- 这项工作推进了人工智能驱动的视频合成领域,提供了个性化的属性.
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