InfiniteDance: Scalable 3D Dance Generation Towards in-the-wild Generalization

ArXi:2603.13375v1 Announce Type: cross Although existing 3D dance generation methods perform well in controlled scenarios, they often struggle to generalize in the wild. When conditioned on unseen music, existing methods often produce unstructured or physically implausible dance, largely due to limited music-to-dance data and restricted model capacity. This work aims to push the frontier of generalizable 3D dance generation by scaling up both data and model design.