SCULPTOR: Skeleton-Consistent Face Creation Using a Learned Parametric Generator

SIGGRAPH Aisa 2022

Zesong Qiu1,*,  Yuwei Li1,*,  Dongming He2,*,  Qixuan Zhang1,3,  Longwen Zhang1,3,  Yinghao Zhang1,  Jingya Wang1,  Lan Xu1,  Xudong Wang2,  Yuyao Zhang1,  Jingyi Yu1

1School of Information Science and Technology, ShanghaiTech University
2Shanghai Ninth People’s Hospital
3Deemos Technology Co., Ltd.

Paper Code Data

Recent years have seen growing interest in 3D human face modeling due to its wide applications in digital human, character generation and animation. Existing approaches overwhelmingly emphasized on modeling the exterior shapes, textures and skin properties of faces, ignoring the inherent correlation between inner skeletal structures and appearance. In this paper, we present SCULPTOR, 3D face creations with Skeleton Consistency Using a Learned Parametric facial generaTOR, aiming to facilitate the easy creation of both anatomically correct and visually convincing face models via a hybrid parametric-physical representation. At the core of SCULPTOR is LUCY, the first large-scale shape-skeleton face dataset in collaboration with plastic surgeons. Named after the fossils of one of the oldest known human ancestors, our LUCY dataset contains high-quality Computed Tomography (CT) scans of the complete human head before and after orthognathic surgeries, which are critical for evaluating surgery results. LUCY consists of 144 scans of 72 subjects (31 male and 41 female), where each subject has two CT scans taken pre- and post-orthognathic operations. Based on our LUCY dataset, we learned a novel skeleton consistent parametric facial generator, SCULPTOR, which can create unique and nuanced facial features that help define a character and at the same time maintain physiological soundness. Our SCULPTOR jointly models the skull, face geometry and face appearance under a unified data-driven framework by separating the depiction of a 3D face into shape blend shape, pose blend shape and facial expression blend shape. SCULPTOR preserves both anatomic correctness and visual realism in facial generation tasks compared with existing methods. Finally, we showcase the robustness and effectiveness of SCULPTOR in various fancy applications unseen before, like archaeological skeletal facial completion, bone-aware character fusion, skull inference from images, face generation with lipo-Level change and facial animations, etc.

Our realistic face generation pipeline with trait effect. Starting with SCULPTOR full template, we randomly generate and procedurally add shape, trait, appearance and expression/pose effects on the neutral template, rendering the 3D face with environment maps.


@article{10.1145/3550454.3555462, author = {Qiu, Zesong and Li, Yuwei and He, Dongming and Zhang, Qixuan and Zhang, Longwen and Zhang, Yinghao and Wang, Jingya and Xu, Lan and Wang, Xudong and Zhang, Yuyao and Yu, Jingyi}, title = {SCULPTOR: Skeleton-Consistent Face Creation Using a Learned Parametric Generator}, year = {2022}, issue_date = {December 2022}, publisher = {Association for Computing Machinery}, address = {New York, NY, USA}, volume = {41}, number = {6}, issn = {0730-0301}, url = {}, doi = {10.1145/3550454.3555462}, journal = {ACM Trans. Graph.}, month = {nov}, articleno = {213}, numpages = {17}, keywords = {face model, anatomical model, parametric learning} }