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English(EN) MOCHI: Motion Enhancement of Collaborative Human-object Interactions

MOCHI框架增强了嘈杂的人与物体交互数据

作者 PulseAugur 编辑部 · [2 个来源] ·

研究人员开发了MOCHI，一个旨在增强协作式人与物体交互（MHOI）场景中嘈杂数据的两阶段框架。该系统首先优化手部抓取，使其在物理上合理且与身体姿势在语义上一致，并将这些优化扩展到完整的交互序列。随后，一个基于扩散的噪声优化框架使用单人运动先验来完善所有参与者的运动，并整合交互信息。MOCHI已在各种MHOI数据集和应用中证明了其有效性，包括基于关键帧的创建和数据增强。 AI

影响 提高了人与物体交互建模的数据质量，可能改进依赖此类数据的AI系统。

排序理由 该集群包含一篇在arXiv上发表的研究论文，详细介绍了用于增强MHOI数据的新框架。

在 arXiv cs.CV 阅读 →

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MOCHI框架增强了嘈杂的人与物体交互数据

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该集群包含一篇在arXiv上发表的研究论文，详细介绍了用于增强MHOI数据的新框架。
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报道来源 [2]

  1. arXiv cs.CV TIER_1 English(EN) · Jiye Lee, Yonghun Choi, Jungdam Won ·

    MOCHI：协作式人与物体交互的运动增强

    arXiv:2606.18243v1 Announce Type: new Abstract: Collaborative human-object interaction shows dynamic and complex movements that require mutual anticipation and continuous adjustment between participants and the shared object. Modeling such collaborative multi-human object interac…

  2. arXiv cs.CV TIER_1 English(EN) · Jungdam Won ·

    MOCHI：协作式人与物交互的运动增强

    Collaborative human-object interaction shows dynamic and complex movements that require mutual anticipation and continuous adjustment between participants and the shared object. Modeling such collaborative multi-human object interaction (MHOI) scenarios requires high-quality data…

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