系统梳理3D数字人构建方法，从先验学习到逼真建模
How to Build Digital Humans? From Priors to Photorealistic Avatars
- 分三阶段构建：学人体表征、个性化建模、驱动动画
- 提出多维度分类体系，涵盖身体部位与先验类型
- 适合刚入门的研究者快速掌握技术脉络
本综述系统介绍可控3D人类角色的构建方法。现有系统通常包含三个阶段：(i) 学习人体外观与动作的先验知识，(ii) 构建个性化角色，(iii) 驱动角色动画。为聚焦重点，本文集中讨论先验学习与角色创建阶段。我们定义了当前角色表示形式，并提出一个多层次分类体系，按身体区域和采用的先验类型对已有工作进行分类。回顾了全身与头部角色的生成方法，以及将身体分解为手部、头发、衣物等组件的分层表示方法。最后，总结共性原理，为新手推荐关键文献，并探讨现存挑战与未来方向。
原文摘要 · Abstract (English)
This state-of-the-art report provides an overview of controllable 3D human avatar creation. We describe current 3D avatar systems, which typically consist of three stages: (i) learning priors of human appearance and motion, (ii) creating a personalized avatar, and (iii) animating the avatar. To limit the scope, we focus on the prior learning and avatar creation stages. We define current avatar representations and introduce a taxonomy that categorizes existing work along multiple axes, including body regions and employed priors. We review methods for full-body and head avatars, as well as layered representations that decompose the body into components such as hands, hair, and garments. Finally, we outline common underlying principles, reference key literature for newcomers, and discuss open challenges and future research directions.
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