Kavli Affiliate: David Muller | Summary:Behavioral Foundation Models (BFMs) offer a promising path toward universal physics-based character control by organizing a rich repertoire of physically plausible behaviors into a latent space, guided by a large-scale motion dataset. While these models excel at time-invariant tasks, such as goal-reaching and state-based reward optimization, their latent space does […]
Continue.. BFMTrack: Latent Sequence Optimization for Physics-Based Motion Tracking with Behavioral Foundation Models