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Plausible 3D Face Wrinkle Generation Using Variational Autoencoders.

作者信息

Deng Qixin, Ma Luming, Jin Aobo, Bi Huikun, Le Binh Huy, Deng Zhigang

出版信息

IEEE Trans Vis Comput Graph. 2022 Sep;28(9):3113-3125. doi: 10.1109/TVCG.2021.3051251. Epub 2022 Jul 29.

DOI:10.1109/TVCG.2021.3051251
PMID:33439847
Abstract

Realistic 3D facial modeling and animation have been increasingly used in many graphics, animation, and virtual reality applications. However, generating realistic fine-scale wrinkles on 3D faces, in particular, on animated 3D faces, is still a challenging problem that is far away from being resolved. In this article we propose an end-to-end system to automatically augment coarse-scale 3D faces with synthesized fine-scale geometric wrinkles. By formulating the wrinkle generation problem as a supervised generation task, we implicitly model the continuous space of face wrinkles via a compact generative model, such that plausible face wrinkles can be generated through effective sampling and interpolation in the space. We also introduce a complete pipeline to transfer the synthesized wrinkles between faces with different shapes and topologies. Through many experiments, we demonstrate our method can robustly synthesize plausible fine-scale wrinkles on a variety of coarse-scale 3D faces with different shapes and expressions.

摘要

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