  Controlling the manner in which a character moves in a real-time animation
system is a challenging task with useful applications. Existing style transfer
systems require access to a reference content motion clip, however, in
real-time systems the future motion content is unknown and liable to change
with user input. In this work we present a style modelling system that uses an
animation synthesis network to model motion content based on local motion
phases. An additional style modulation network uses feature-wise
transformations to modulate style in real-time. To evaluate our method, we
create and release a new style modelling dataset, 100STYLE, containing over 4
million frames of stylised locomotion data in 100 different styles that present
a number of challenges for existing systems. To model these styles, we extend
the local phase calculation with a contact-free formulation. In comparison to
other methods for real-time style modelling, we show our system is more robust
and efficient in its style representation while improving motion quality.
