研究人员开发了一种新的全身虚拟形象动画方法，特别关注宽松服装的逼真变形。他们的方法通过一个基于Transformer的解码器和一个动力学残差潜在变量来增强姿态条件化的3D高斯虚拟形象。该潜在变量组件捕捉超越简单姿态的时间变化，根据历史、惯性和接触力进行演变，从而以最小的计算开销产生连贯且依赖于历史的运动。 AI
影响 引入了一种新颖的虚拟形象动画方法，提高了服装等动态元素的真实感，这可能增强虚拟环境和数字内容创作。
排序理由 该集群包含一篇详细介绍虚拟形象动画新方法的学术论文。
在 Hugging Face Daily Papers 阅读 →
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Pose-driven full-body avatars built on neural rendering produce high-quality novel views of a captured subject. Yet loose clothing and other dynamic elements deform in ways pose alone cannot explain: the same pose can correspond to many different states, because their motion depe…
Pose-driven full-body avatars built on neural rendering produce high-quality novel views of a captured subject. Yet loose clothing and other dynamic elements deform in ways pose alone cannot explain: the same pose can correspond to many different states, because their motion depe…