arXiv:2504.16722cs.CVcs.AI2025-04被引 1

通过分阶段锚点引导,实现精准可控的人体动作生成。

PMG: Progressive Motion Generation via Sparse Anchor Postures Curriculum Learning

  • 用稀疏锚点姿态与轨迹解耦控制,提升动作精度。
  • 分阶段课程学习策略使训练更稳定,生成动作更自然。
  • 支持单/双控制模式,适合游戏与动画中的个性化动作设计。

在计算机动画、游戏设计和人机交互中,生成符合用户意图的人体动作仍是重大挑战。现有方法存在明显局限:文本引导仅提供高层语义,难以准确描述复杂动作;基于轨迹的方法虽能直观表达整体运动方向,却难生成精确或定制化动作;而锚点姿态引导方法通常只能合成简单动作模式。为此,我们提出一种新框架——ProMoGen(渐进式动作生成),将轨迹引导与稀疏锚点动作控制相结合。全局轨迹确保空间方向与位移的一致性,而稀疏锚点仅提供精确动作指导,不包含位移信息。这种解耦设计允许对两方面独立优化,实现更高可控性、保真度与复杂度的动作合成。ProMoGen 在统一训练过程中支持双控与单控两种范式。此外,由于直接从稀疏动作中学习本身不稳定,我们引入SAP-CL(稀疏锚点姿态课程学习)策略,逐步增加引导锚点数量,从而实现更精确、稳定的收敛。大量实验表明,ProMoGen 在预设轨迹与任意锚点帧引导下,均能生成生动多样的动作。该方法可无缝融合个性化动作与结构化引导,在多种控制场景中显著优于当前最优方法。

原文摘要 · Abstract (English)

In computer animation, game design, and human-computer interaction, synthesizing human motion that aligns with user intent remains a significant challenge. Existing methods have notable limitations: textual approaches offer high-level semantic guidance but struggle to describe complex actions accurately; trajectory-based techniques provide intuitive global motion direction yet often fall short in generating precise or customized character movements; and anchor poses-guided methods are typically confined to synthesize only simple motion patterns. To generate more controllable and precise human motions, we propose \textbf{ProMoGen (Progressive Motion Generation)}, a novel framework that integrates trajectory guidance with sparse anchor motion control. Global trajectories ensure consistency in spatial direction and displacement, while sparse anchor motions only deliver precise action guidance without displacement. This decoupling enables independent refinement of both aspects, resulting in a more controllable, high-fidelity, and sophisticated motion synthesis. ProMoGen supports both dual and single control paradigms within a unified training process. Moreover, we recognize that direct learning from sparse motions is inherently unstable, we introduce \textbf{SAP-CL (Sparse Anchor Posture Curriculum Learning)}, a curriculum learning strategy that progressively adjusts the number of anchors used for guidance, thereby enabling more precise and stable convergence. Extensive experiments demonstrate that ProMoGen excels in synthesizing vivid and diverse motions guided by predefined trajectory and arbitrary anchor frames. Our approach seamlessly integrates personalized motion with structured guidance, significantly outperforming state-of-the-art methods across multiple control scenarios.

动作生成锚点控制课程学习

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