3DFaceShop:明确可控制的3D感知肖像生成系统
IEEE transactions on visualization and computer graphics
|October 17, 2023
概括
这项研究引入了一个新的网络,用于从照片中生成可控制的3D感知肖像. 该方法确保了多视图一致性和现实的表达动画,优于现有技术.
科学领域:
- 计算机视觉 计算机视觉
- 计算机图形 计算机图形
- 人工智能的人工智能
背景情况:
- 传统的化身创作是昂贵的.
- 生成模型提供从照片直接学习.
- 可控制的生成模型在多视图一致性方面扎,特别是在大型姿势方面.
研究的目的:
- 提出一个网络,用于生成具有3D意识的肖像,对姿势,身份,表达和照明进行语义控制.
- 为了应对生成肖像合成中多视图一致性的挑战.
- 为了提高生成的3D肖像的现实性和可控性.
主要方法:
- 使用神经场景表示用于3D感知肖像建模.
- 使用参数面模型进行显式控制.
- 通过从语义字段中分割动态和静态区域,引入用于无表达式动画的体积混合策略.
主要成果:
- 与以前的方法相比,在生成真实的肖像时实现了更高的性能.
- 在自然照明条件下产生生动的表达,具有自由视角染.
- 展示了对真实图像和域外数据的概括.
结论:
- 拟议的网络有效地产生可控制的,具有高视觉保真度的3D感知肖像.
- 音量混合策略在表达式动画中成功地解决了非面部区域的不一致性.
- 该方法对数字人类和虚拟现实中的现实应用具有重大前景.
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