SMooDi: Stylized Motion Diffusion Model

Lei Zhong, Yiming Xie, Varun Jampani, Deqing Sun, Huaizu Jiang* ;

"We introduce a novel Stylized Motion Diffusion model, dubbed , to generate stylized motion driven by content texts and style motion sequences. Unlike existing methods that either generate motion of various content or transfer style from one sequence to another, can rapidly generate motion across a broad range of content and diverse styles. To this end, we tailor a pre-trained text-to-motion model for stylization. Specifically, we propose style guidance to ensure that the generated motion closely matches the reference style, alongside a lightweight style adaptor that directs the motion towards the desired style while ensuring realism. Experiments across various applications demonstrate that our proposed framework outperforms existing methods in stylized motion generation. Project Page: https://neu-vi.github.io/SMooDi/"