Jan. 31, 2024, 3:43 p.m. | Qingcheng Zhao Pengyu Long Qixuan Zhang Dafei Qin Han Liang Longwen Zhang Yingliang Zhang Jing

cs.CV updates on arXiv.org arxiv.org

The synthesis of 3D facial animations from speech has garnered considerable attention. Due to the scarcity of high-quality 4D facial data and well-annotated abundant multi-modality labels, previous methods often suffer from limited realism and a lack of lexible conditioning. We address this challenge through a trilogy. We first introduce Generalized Neural Parametric Facial Asset (GNPFA), an efficient variational auto-encoder mapping facial geometry and images to a highly generalized expression latent space, decoupling expressions and identities. Then, we utilize GNPFA to …

animation animations attention challenge cs.cv cs.gr data generalized guidance labels parametric quality speech synthesis through

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