文本引导的组合式3D虚拟形象生成与编辑
Text-Guided Generation and Editing of Compositional 3D Avatars
AI总结：
提出组合式3D虚拟形象生成与编辑方法TECA，结合3D网格与NeRF分别表示面部与毛发配饰，实现高真实感且支持发型等特征迁移编辑。
摘要：
我们的目标是仅使用文本描述创建带有头发和配饰的逼真3D面部虚拟形象。尽管这一挑战近期引起了广泛关注，但现有方法要么缺乏真实感，产生不真实的形状，要么不支持编辑（例如修改发型）。我们认为现有方法存在局限的原因在于它们采用了单一的整体建模方法，对头部、面部、头发和配饰使用单一表示。我们观察到，例如头发和面部具有非常不同的结构特征，它们能从不同的表示中获益。基于这一洞察，我们使用组合模型生成虚拟形象，其中头部、面部和上半身使用传统的3D网格表示，而头发、服装和配饰使用神经辐射场（NeRF）表示。基于模型的网格表示为面部区域提供了强大的几何先验，在提高真实感的同时实现了对人物外观的编辑。通过使用NeRF来表示其余组件，我们的方法能够建模和合成具有复杂几何和外观的部件，如卷发和蓬松的围巾。我们的新系统从文本描述合成这些高质量的组合虚拟形象。实验结果表明，我们的方法——文本引导的组合虚拟形象生成与编辑（TECA）——生成的虚拟形象比近期方法的更逼真，同时由于其组合特性而具备可编辑性。例如，我们的TECA能够在虚拟形象之间无缝迁移发型、围巾和其他配饰等组合特征。这一能力支持虚拟试穿等应用。
英文摘要：
Our goal is to create a realistic 3D facial avatar with hair and accessories using only a text description. While this challenge has attracted significant recent interest, existing methods either lack realism, produce unrealistic shapes, or do not support editing, such as modifications to the hairstyle. We argue that existing methods are limited because they employ a monolithic modeling approach, using a single representation for the head, face, hair, and accessories. Our observation is that the hair and face, for example, have very different structural qualities that benefit from different representations. Building on this insight, we generate avatars with a compositional model, in which the head, face, and upper body are represented with traditional 3D meshes, and the hair, clothing, and accessories with neural radiance fields (NeRF). The model-based mesh representation provides a strong geometric prior for the face region, improving realism while enabling editing of the person's appearance. By using NeRFs to represent the remaining components, our method is able to model and synthesize parts with complex geometry and appearance, such as curly hair and fluffy scarves. Our novel system synthesizes these high-quality compositional avatars from text descriptions. The experimental results demonstrate that our method, Text-guided generation and Editing of Compositional Avatars (TECA), produces avatars that are more realistic than those of recent methods while being editable because of their compositional nature. For example, our TECA enables the seamless transfer of compositional features like hairstyles, scarves, and other accessories between avatars. This capability supports applications such as virtual try-on.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
