DexFlow: A Unified Approach for Dexterous Hand Pose Retargeting and Interaction

DexFlow: A Unified Approach for Dexterous Hand Pose Retargeting and Interaction Xiaoyi Lin 1, Kunpeng Y ao 2, Lixin Xu 3,Xueqiang Wang 4,Xuetao Li 1,Y uchen Wang 1,Miao Li 4, Abstract -- Despite advances in hand-object interaction modeling, generating realistic dexterous manipulation data for robotic hands remains a challenge. Retargeting methods often suffer from low accuracy and fail to account for hand-object interactions, leading to artifacts like interpenetration. Generative methods, lacking human hand priors, produce limited and unnatural poses. We propose a data transformation pipeline that combines human hand and object data from multiple sources for high-precision retargeting. Our approach uses a differential loss constraint to ensure temporal consistency and generates contact maps to refine hand-object interactions.