AgenticFocus: Object-Preserving Mixed Reality Synthesis from Human FPV Video for Dexterous Humanoid Learning

• URL: http://arxiv.org/abs/2607.08857v2
• Date: Mon, 13 Jul 2026 16:37:13 GMT
• Title: AgenticFocus: Object-Preserving Mixed Reality Synthesis from Human FPV Video for Dexterous Humanoid Learning
• Abstract summary: We introduce AgenticFocus, a Mixed Reality synthesis pipeline that converts ordinary first-person-view human videos into robot-trainable demonstrations.<n>The resulting dataset pairs focused visual observations with synchronized robot actions and states.<n>AgenticFocus achieves trajectory error and smoother wrist motion than cross-embodiment baselines, with scores of -5.18 versus -5.56 and -6.05.
• Score: 2.0979009566413946
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Human egocentric video is a scalable supervision source for humanoid policy learning, but current pipelines struggle with hand-object occlusion, oversimplified motion, or specialized capture hardware. We introduce AgenticFocus, a Mixed Reality synthesis pipeline that converts ordinary first-person-view human videos into robot-trainable demonstrations by restoring occluded object geometry, reconstructing full-hand motion, and retargeting it to a humanoid embodiment through camera-relative alignment and layered compositing. The resulting dataset pairs focused visual observations with synchronized robot actions and states. AgenticFocus achieves lower trajectory error and smoother wrist motion than cross-embodiment baselines, with SPARC scores of -5.18 versus -5.56 and -6.05.

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