FaceScape: A Large-Scale High Quality 3D Face Dataset and Detailed Riggable 3D Face Prediction

Haotian Yang, Hao Zhu, Yanru Wang, Mingkai Huang, Qiu Shen, Ruigang Yang, Xun Cao
2020 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)  
FaceScape dataset -18,760 topologically uniformed detailed 3D faces detailed riggable face prediction 938 identities source image rigged faces predicted face Figure 1: We present FaceScape, a large-scale detailed 3D face dataset consisting of 18,760 textured 3D face models with pore-level geometry. By learning dynamic details from FaceScape, we present a novel algorithm to predict from a single image a detailed rigged 3D face model that can generate various expressions with high geometric details.
doi:10.1109/cvpr42600.2020.00068 dblp:conf/cvpr/Yang0WHSYC20 fatcat:w3mexbmc5bfl7gui2ma6xouv3i