OATH: Object-Agnostic Tracking for Dexterous Hands, Enabling Rapid Physics-based Retargeting

Retargeting human demonstrations into dynamically feasible dexterous hand trajectories requires resolving complex contact physics, yet current methods either omit physical constraints or rely on computationally expensive sampling-based optimization in simulation. Reinforcement learning has previousl