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English(EN) MUGEN: A Unified Framework for Efficient Motion Understanding and Generation

MUGEN框架通过连续潜在变量统一运动理解和生成

研究人员推出MUGEN,一个新颖的统一框架,旨在实现高效的运动理解和生成。与依赖离散运动码本的先前方法不同,MUGEN利用从连续潜在槽中进行的一次抽取,消除了量化限制并提高了生成质量。这种方法允许单个自适应长度的自编码器压缩不同长度的运动,而语言模型生成的潜在变量可用于文本到运动生成和运动到文本理解任务。MUGEN在HumanML3D和SnapMoGen等基准测试中,在FID、检索精度、CIDEr和BLEU@4等各种指标上均展现出最先进的性能,同时显著降低了解码成本。 AI

影响 该框架有望加速开发更复杂的AI系统,这些系统能够理解物理环境中的人类行为并与之互动。

排序理由 该集群包含一篇详细介绍AI运动理解和生成新框架的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

MUGEN框架通过连续潜在变量统一运动理解和生成

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该集群包含一篇详细介绍AI运动理解和生成新框架的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Zhankai Ye, Yukai Jin, Bingyang Wei, Bofan Li, Yusen Wu, Fangyi Li, Shangqian Gao, Xin Liu ·

    MUGEN:一个用于高效运动理解与生成的统一框架

    arXiv:2607.27581v1 Announce Type: new Abstract: Grounding human motion in language, and language in motion, is a central step toward physical AI systems that can understand, generate, and communicate human behavior. Unified motion--language systems first coupled the two direction…