主管(地质)
计算机科学
面子(社会学概念)
人工智能
参数化复杂度
构造(python库)
管道(软件)
三维模型
计算机视觉
影子(心理学)
模式识别(心理学)
算法
地质学
心理学
社会科学
地貌学
社会学
程序设计语言
心理治疗师
作者
Jie Zhang,Yan Luximon,Lei Zhu,Ping Li
标识
DOI:10.1145/3574131.3574435
摘要
3D head completion aims at recovering accurate 3D full-head geometry from 2D face images or 3D face scans. Previous 3D shape reconstruction studies primarily focused on the facial region, but ignored the scalp region. Moreover, as critical foundations in 3D head completion, powerful 3D head morphable models, however, are scarce. In this paper, we construct 3D comprehensive morphable models (3DCMM) of human faces and scalps, and develop a novel 3DCMM-based stepwise 3D full-head creation pipeline: reconstructing face regions firstly, and then completing scalp regions. Firstly, large-scale 3D heads from 2,528 identities were parameterized to construct powerful 3DCMM as our foundations. Then, a 3DCMM-based supervised converting method was presented to predict an accurate scalp region from a facial region and produce full-head geometry. Extensive experiments and comparisons demonstrated that our 3DCMM possesses better quality and descriptive power. Benefiting from this, our model-based 3D head completion method has higher accuracy than model-based fitting method.
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