  We present a novel approach named OmniControl for incorporating flexible
spatial control signals into a text-conditioned human motion generation model
based on the diffusion process. Unlike previous methods that can only control
the pelvis trajectory, OmniControl can incorporate flexible spatial control
signals over different joints at different times with only one model.
Specifically, we propose analytic spatial guidance that ensures the generated
motion can tightly conform to the input control signals. At the same time,
realism guidance is introduced to refine all the joints to generate more
coherent motion. Both the spatial and realism guidance are essential and they
are highly complementary for balancing control accuracy and motion realism. By
combining them, OmniControl generates motions that are realistic, coherent, and
consistent with the spatial constraints. Experiments on HumanML3D and KIT-ML
datasets show that OmniControl not only achieves significant improvement over
state-of-the-art methods on pelvis control but also shows promising results
when incorporating the constraints over other joints.
