CoMusion: Towards Consistent Stochastic Human Motion Prediction via Motion Diffusion

Understand

Stochastic Human Motion Prediction (HMP) aims to predict multiple possible future human pose sequences from observed ones.

• Most prior works learn motion distributions through encoding-decoding in the latent space, which does not preserve motion's spatial-temporal structure.
• While effective, these methods often require complex, multi-stage training and yield predictions that are inconsistent with the provided history and can be physically unrealistic.
• To address these issues, we propose CoMusion, a single-stage, end-to-end diffusion-based stochastic HMP framework.