Niklas Berndt, Xianghui Xie, Enes Duran, Yixiao Wang, Gerard Pons-Moll · 2026 · arXiv
DOI: 10.48550/arXiv.2610.31299 · open-access PDF
La síntesis de interacciones de mano-objeto físicamente fundamentadas es importante para VR/AR, juegos y robótica, pero sigue siendo un desafío porque la dinámica de contacto sutil, las geometrías de objetos diversas y las trayectorias de meta deben ser respetadas conjuntamente mientras se mantienen los alcances naturales. Los métodos existentes o bien rastrean las trayectorias de mocap con transferencia limitada a objetos nuevos, o se basan en preórdenes generativos únicamente manuales que no capturan el movimiento de mano-objeto combinado, sacrificando la fidelidad del contacto y la eficiencia de la muestra.
Machine translation (Meta M2M100); the English original follows.
Synthesizing physically grounded dexterous hand-object interactions is important for VR/AR, gaming, and robotics, yet remains challenging because subtle contact dynamics, diverse object geometries, and target trajectories must be jointly respected while maintaining natural grasps. Existing methods either track mocap trajectories with limited transfer to novel objects, or rely on hand-only generative priors that fail to capture coupled hand-object motion, sacrificing contact fidelity and sample efficiency. To tackle these challenges, we introduce PiHand, a Physically grounded Interaction-aware
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