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    UMR team announces open code for transferring human motion across humanoid bodies

    The team says Unified Motion Retargeting learns matches between point clouds and supports locomotion and contact-rich data.

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    TLDR

    The team behind Unified Motion Retargeting (UMR) says its method transfers human motion across different humanoid bodies by learning dense correspondences between point cloudsโ€”sets of points representing shapes. The announcement says UMR supports locomotion and contact-rich data, and that the code is open.

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    2 Sources, first seen 19d ago

    Combined views

    49.8K

    2 Sources, first seen 19d ago

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    19d ago
    first seen 19d ago
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    27 comments
    391 saves
    108 reposts

    Sentiment

    Positiveโ€”โ€”Negative

    Summary

    Not enough discussion yet.

    No sentiment analysis available yet.

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    2 Sources

    @Runyi_Ingrid_Yu๐ŸŽ‰ Excited to share our new work: UMR! ๐ŸŽ‰ Unified Motion Retargeting (UMR) learns dense point-cloud correspondences to transfer human motion across diverse humanoid embodiments. It supports locomotion and contact-rich data. Code is now open! ๐ŸŒ: https://hanyang9.github.io/UMR/
    @ScobleizerRT @Runyi_Ingrid_Yu: ๐ŸŽ‰ Excited to share our new work: UMR! ๐ŸŽ‰ Unified Motion Retargeting (UMR) learns dense point-cloud correspondences tโ€ฆ

    2 Sources

    @Runyi_Ingrid_Yu๐ŸŽ‰ Excited to share our new work: UMR! ๐ŸŽ‰ Unified Motion Retargeting (UMR) learns dense point-cloud correspondences to transfer human motion across diverse humanoid embodiments. It supports locomotion and contact-rich data. Code is now open! ๐ŸŒ: https://hanyang9.github.io/UMR/
    @ScobleizerRT @Runyi_Ingrid_Yu: ๐ŸŽ‰ Excited to share our new work: UMR! ๐ŸŽ‰ Unified Motion Retargeting (UMR) learns dense point-cloud correspondences tโ€ฆ