  Text-to-motion synthesis is a crucial task in computer vision. Existing
methods are limited in their universality, as they are tailored for
single-person or two-person scenarios and can not be applied to generate
motions for more individuals. To achieve the number-free motion synthesis, this
paper reconsiders motion generation and proposes to unify the single and
multi-person motion by the conditional motion distribution. Furthermore, a
generation module and an interaction module are designed for our FreeMotion
framework to decouple the process of conditional motion generation and finally
support the number-free motion synthesis. Besides, based on our framework, the
current single-person motion spatial control method could be seamlessly
integrated, achieving precise control of multi-person motion. Extensive
experiments demonstrate the superior performance of our method and our
capability to infer single and multi-human motions simultaneously.
