MotionDiffuser: Controllable Multi-Agent Motion Prediction Using Diffusion

Waymo LLC Figure 1 . MotionDiffuser is a learned representation for the distribution of multi-agent trajectories based on diffusion models. During inference, samples from the predicted joint future distribution are first drawn i.i.d. from a random normal distribution (leftmost column), and gradually denoised using a learned denoiser into the final predictions (rightmost column). Diffusion allows us to learn a diverse, multimodal distribution over joint outputs (top right). Furthermore, guidance in the form of a differentiable cost function can be applied at inference time to obtain results satisfying additional priors and constraints (bottom right).