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MotionGPT-2 使用语言模型在人体运动生成方面取得进展

研究人员开发了 MotionGPT-2,一个大型运动-语言模型,旨在根据文本描述生成和理解人体运动。该模型将文本和姿势等多模态输入集成到一个统一的提示系统中,使其能够处理各种运动相关任务。MotionGPT-2 采用新颖的运动离散化框架,确保对身体和手部运动进行细粒度控制,在生成、字幕和补全任务中表现出有效性。 AI

影响 这些模型在根据文本生成逼真的人体运动方面取得了最先进的成果,在动画、游戏和虚拟现实领域具有潜在应用。

排序理由 该集群包含两篇详细介绍运动生成新模型的学术论文。

在 arXiv cs.CV 阅读 →

AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →

MotionGPT-2 使用语言模型在人体运动生成方面取得进展

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该集群包含两篇详细介绍运动生成新模型的学术论文。
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报道来源 [2]

  1. arXiv cs.CV TIER_1 English(EN) · Yuan Wang, Di Huang, Yaqi Zhang, Wanli Ouyang, Jile Jiao, Xuetao Feng, Dan Xu, Shixiang Tang ·

    MotionGPT-2:用于运动生成和理解的通用运动语言模型

    arXiv:2410.21747v2 Announce Type: replace Abstract: Generating lifelike human motions from descriptive texts has experienced remarkable research focus in the recent years, propelled by the emerging requirements of digital humans.Despite impressive advances, existing approaches ar…

  2. arXiv cs.CV TIER_1 English(EN) · Taeryung Lee, Fabien Baradel, Thomas Lucas, Kyoung Mu Lee, Gregory Rogez ·

    T2LM:从多句话生成长期三维人体运动

    arXiv:2406.00636v2 Announce Type: replace Abstract: In this paper, we address the challenging problem of long-term 3D human motion generation. Specifically, we aim to generate a long sequence of smoothly connected actions from a stream of multiple sentences (i.e., paragraph). Pre…