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arXiv Robotics — research abstracts· Nghia Le (Hann), Khang Nguyen (Hann), Ba Long Tran (Hann), Thi Quynh Nhu Pham (Hann), Binh Nguyen (Hann), Tuong Do (Hann), Erman Tjiputra (Hann), Hoan Nguyen (Hann), Tung D. Ta (Hann), Baoru Huang (Hann), Hai-Nguyen (Hann), Nguyen (Hann), Anh Nguyen·· 5 hours agoSignalEditorial score85

Mimetic Embodiment Transfer of Human-Humanoid Interaction from In-the-Wild Videos

Mimetic Embodiment Transfer of Human-Humanoid Interaction from In-the-Wild Videos

Summary

This research proposes HumiTransfer, a framework that converts real-world human-human interaction videos into physically plausible human-humanoid interactions. The method reconstructs 3D human motion and transfers interactions to humanoid robots like the Unitree R1 Edu and HighTorque Mini-hi, resulting in the HumiMimic dataset. The approach preserves inter-body relationships and contact accuracy, and is validated through real robot deployments.

Editorial context

This paper introduces HumiTransfer, a framework for transferring human-human interaction from in-the-wild videos to humanoid robots, achieving better motion fidelity and preserving inter-body relationships compared to existing methods.

Source: arXiv Robotics — research abstracts · Read original article ↗

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What the source reports

Publisher-reported claims, with original evidence. These results have not been independently verified by RoboSignal.

Reported numbers

  • frames

    ≈500,000 frames

    View original evidence
    rections and anatomical offsets to prioritize interaction-critical inter-body relationships, while post-retargeting optimization enforces balance, contact, and collision avoidance. Subsequently, we apply HumiTransfer to 1,200 in-the-wild videos, producing approximately 500,000 frames of diverse interactions for the 26-DoF Unitree R1 Edu and the 23-DoF HighTorque Mini-hi humanoid robot, resulting in our HumiMimic data
    Open source S4
  • videos

    1,200

    View original evidence
    rections and anatomical offsets to prioritize interaction-critical inter-body relationships, while post-retargeting optimization enforces balance, contact, and collision avoidance. Subsequently, we apply HumiTransfer to 1,200 in-the-wild videos, producing approximately 500,000 frames of diverse interactions for the 26-DoF Unitree R1 Edu and the 23-DoF HighTorque Mini-hi humanoid robot, resulting in our HumiMimic data
    Open source S4
  • degrees of freedom

    26

    View original evidence
    rections and anatomical offsets to prioritize interaction-critical inter-body relationships, while post-retargeting optimization enforces balance, contact, and collision avoidance. Subsequently, we apply HumiTransfer to 1,200 in-the-wild videos, producing approximately 500,000 frames of diverse interactions for the 26-DoF Unitree R1 Edu and the 23-DoF HighTorque Mini-hi humanoid robot, resulting in our HumiMimic data
    Open source S4
  • degrees of freedom

    23

    View original evidence
    rections and anatomical offsets to prioritize interaction-critical inter-body relationships, while post-retargeting optimization enforces balance, contact, and collision avoidance. Subsequently, we apply HumiTransfer to 1,200 in-the-wild videos, producing approximately 500,000 frames of diverse interactions for the 26-DoF Unitree R1 Edu and the 23-DoF HighTorque Mini-hi humanoid robot, resulting in our HumiMimic data
    Open source S4
  • paper: not_reported
  • code: not_reported
  • weights: not_reported
  • dataset: not_reported
Source excerpts and review record

Automatically extracted; no manual editorial approval recorded.

rections and anatomical offsets to prioritize interaction-critical inter-body relationships, while post-retargeting optimization enforces balance, contact, and collision avoidance. Subsequently, we apply HumiTransfer to 1,200 in-the-wild videos, producing approximately 500,000 frames of diverse interactions for the 26-DoF Unitree R1 Edu and the 23-DoF HighTorque Mini-hi humanoid robot, resulting in our HumiMimic data

Open source S4

set. Across both robots, HumiTransfer achieves superior motion fidelity, preserves inter-body relationships, and maintains contact accuracy compared with existing baselines. Moreover, we demonstrate that HumiMimic supports motion generation methods for synthesizing interactive humanoid motions following a human partner. Finally, our real robot deployments confirm the physical executability of the transferred motions

Open source S5

Source:arXiv Robotics — research abstracts · arxiv.org

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