GNM头部：一种人类头部的生成式人体测量模型
GNM Head: A Generative aNthropometric Model of the human head
- Google（谷歌）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
介绍一种名为GNM的人类头部生成式人体测量模型，基于高分辨率3D扫描数据库及特定解剖学样本构建，涵盖多部位，详细说明模型架构等，展示其在拟合3D面部扫描时的最优性能并公开完整框架。
AI中文摘要：
人体头部的参数模型是计算机视觉和图形学中传统用于动画、渲染和重建的重要工具。近期，它们在生成式大型视觉模型中作为关键的条件信号，实现对生成图像的紧密空间控制。然而，现有公开模型在解剖学范围上通常有限，仅对外部几何形状建模，忽略口腔和眼部结构，且常因低质量输入数据集导致几何质量下降。本报告介绍了一种名为生成式人体测量模型（GNM）的新参数模型，它涵盖头部、面部、颈部、眼球、牙齿和舌头，基于高分辨率3D扫描的广泛数据库以及高质量特定解剖学的艺术家制作样本构建。报告详细说明了数据来源、模型架构，包括眼部和口腔结构的专门子模型，并展示了其在拟合目标3D面部扫描时的最优性能。为促进社区创新，完整的GNM框架已公开。
英文摘要：
Parametric models of the human head are essential tools traditionally used in computer vision and graphics for animation, rendering, and reconstruction. More recently, they serve as crucial conditioning signals within generative large vision models, allowing for tight spatial control of generated imagery. However, existing publicly available models are typically limited in anatomical scope, modeling only outer geometry while ignoring intra-oral and ocular structures, and frequently suffer from reduced geometric quality stemming from low-fidelity input datasets. In this report we introduce a new parametric model dubbed Generative aNthropometric Model (GNM), named as a homophone of the human genome. GNM encompasses the head, face, neck, eyeballs, teeth, and tongue, and it is built on an extensive database of high-resolution 3D scans combined with high-quality anatomy specific artist-made samples. This report details the data provenance, the model architecture including the specialized sub-models for the ocular and intra-oral structures, and shows its SotA performance on fitting target 3D face scans. To foster community innovation, the complete GNM framework is made publicly available.
