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English(EN) Compact Motion Embeddings for Feed-forward Unified Human Animation

FUHA模型学习紧凑运动嵌入，实现实时人类动画

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了FUHA，一种新颖的前馈Transformer模型，专为实时人类动画设计。FUHA学习紧凑的运动嵌入，捕捉面部、手部和身体的关节，同时将运动与外观解耦。这种方法在推理过程中无需外部姿态估计器或参数化身体模型。该模型性能令人印象深刻，在单个RTX 4090 GPU上以512x512分辨率运行时速度高达38.9 FPS，并在自我重演指标上优于基线。 AI

影响 为游戏、电影和虚拟现实等应用提供更高效、更逼真的人类动画。

排序理由 这是一篇详细介绍新模型及其性能的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CV 阅读 →

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FUHA模型学习紧凑运动嵌入，实现实时人类动画

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报道来源 [1]

  1. arXiv cs.CV TIER_1 English(EN) · Seonwook Park, Hyunsoo Cha, Amrita Mazumdar, Shengze Wang, Tianye Li, Hanbyul Joo, Koki Nagano, Shalini De Mello ·

    用于前馈统一人体动画的紧凑运动嵌入

    arXiv:2611.07481v1 Announce Type: new Abstract: Animating a reference image with a driver's motion requires a motion representation that captures face, hand, and body articulation but excludes the driver's appearance. Most body animation methods take motion from external pose est…

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