Feb. 27, 2024, 5:48 a.m. | Chuan Guo, Yuxuan Mu, Xinxin Zuo, Peng Dai, Youliang Yan, Juwei Lu, Li Cheng

cs.CV updates on arXiv.org arxiv.org

arXiv:2401.13505v2 Announce Type: replace
Abstract: Human motion stylization aims to revise the style of an input motion while keeping its content unaltered. Unlike existing works that operate directly in pose space, we leverage the latent space of pretrained autoencoders as a more expressive and robust representation for motion extraction and infusion. Building upon this, we present a novel generative model that produces diverse stylization results of a single motion (latent) code. During training, a motion code is decomposed into two …

arxiv cs.cv generative human space type

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