通过模块化身体部位相控实现可控的文本到运动生成
Controllable Text-to-Motion Generation via Modular Body-Part Phase Control
AI总结：
本文提出模块化身体部位相控方法，通过紧凑的标量相界面实现局部化编辑，保留运动整体一致性，提供可控的文本到运动生成方案。
摘要：
文本到运动（T2M）生成正成为动画和交互虚拟角色的实用工具。然而，保持整体运动一致性的同时修改特定身体部位仍具挑战性。现有方法通常依赖于繁琐的高维关节约束（如轨迹），阻碍了用户友好和迭代优化。为此，我们提出模块化身体部位相控，一种即插即用的框架，通过紧凑的标量相界面实现结构化局部编辑。通过将身体部位潜在运动通道建模为具有幅度、频率、相位偏移和偏移的正弦相信号，我们提取出可解释的代码，捕捉部分特定动态。模块化相控制网分支然后通过残差特征调制注入此信号，无缝解耦控制与生成核心。在扩散和流基模型上的实验表明，我们的方法提供了可预测且细粒度的运动幅度、速度和时间控制。它保持了全局运动一致性，并提供了一种可控T2M生成的实用范式。项目页面：https://jixiii.github.io/bp-phase-project-page/
英文摘要：
Text-to-motion (T2M) generation is becoming a practical tool for animation and interactive avatars. However, modifying specific body parts while maintaining overall motion coherence remains challenging. Existing methods typically rely on cumbersome, high-dimensional joint constraints (e.g., trajectories), which hinder user-friendly, iterative refinement. To address this, we propose Modular Body-Part Phase Control, a plug-and-play framework enabling structured, localized editing via a compact, scalar-based phase interface. By modeling body-part latent motion channels as sinusoidal phase signals characterized by amplitude, frequency, phase shift, and offset, we extract interpretable codes that capture part-specific dynamics. A modular Phase ControlNet branch then injects this signal via residual feature modulation, seamlessly decoupling control from the generative backbone. Experiments on both diffusion- and flow-based models demonstrate that our approach provides predictable and fine-grained control over motion magnitude, speed, and timing. It preserves global motion coherence and offers a practical paradigm for controllable T2M generation. Project page: https://jixiii.github.io/bp-phase-project-page/
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
