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FaceScape: A Large-Scale High Quality 3D Face Dataset and Detailed Riggable 3D Face Prediction
2020
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
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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