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    Yuxuan Kuang shares Dex4D dexterous manipulation method

    Yuxuan Kuang from CMU and NVIDIA shares a task-agnostic point track policy for sim-to-real transfer.

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    1 Source, 224d ago, first seen 224d ago

    TLDR

    Yuxuan Kuang posted about Dex4D. The method targets generalizable sim-to-real dexterous manipulation through a task-agnostic point track policy and video generation planners. His tweet asks how to equip robotic hands with skills that hold across objects, tasks, scenes, camera views, and perturbations. He attached a 10-second split-screen video montage showing four robotic manipulations. The announcement comes from the author of the work.

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    31.4K

    1 Source, first seen 224d ago

    Combined views

    31.4K

    1 Source, first seen 224d ago

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    1 comments
    67 saves
    33 reposts

    Sentiment

    Positiveโ€”โ€”Negative

    Summary

    Not enough discussion yet.

    No sentiment analysis available yet.

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    1 Source

    @yuxuank02How to enable dexterous hands with manipulation capabilities that work across diverse objects, tasks, scenes, camera views, and external perturbations? Excited to share Dex4D, a method for generalizable sim-to-real dexterous manipulation via a task-agnostic point track policy and video generation planners! NO parallel grippers, NO teleop! Project page: https://dex4d.github.io/ ๐Ÿงต๐Ÿ‘‡ 0/10 #Robotics #EmbodiedAI #Manipulation #AI #ComputerVision

    1 Source

    @yuxuank02How to enable dexterous hands with manipulation capabilities that work across diverse objects, tasks, scenes, camera views, and external perturbations? Excited to share Dex4D, a method for generalizable sim-to-real dexterous manipulation via a task-agnostic point track policy and video generation planners! NO parallel grippers, NO teleop! Project page: https://dex4d.github.io/ ๐Ÿงต๐Ÿ‘‡ 0/10 #Robotics #EmbodiedAI #Manipulation #AI #ComputerVision