  We introduce a novel Stylized Motion Diffusion model, dubbed SMooDi, 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, SMooDi 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.
