Sparse anchors provide a compact interface for human motion authoring: users specify a few root positions, planar trajectory samples, or body-point targets, while the system synthesizes the full-body motion that completes the under-specified intent. We present AnchorRoute, a sparse-anchor motion synthesis framework that uses anchors as a shared scaffold for both generation and refinement. Before generation, AnchorRoute converts sparse anchors into anchor-condition features and injects the resulting condition memory into a frozen Transition Masked Diffusion prior through AnchorKV and dual-context conditioning. This preserves the generation quality of the pretrained text-to-motion prior while learning sparse spatial control. After generation, the same anchors are evaluated as residuals: their timestamps define refinement intervals, and their residuals determine where correction should be concentrated. RouteSolver then refines the motion by projecting soft-token updates onto anchor-defined piecewise-affine interval bases. This couples generation-time anchor conditioning with residual-routed refinement under one anchor scaffold. AnchorRoute supports root-3D, planar-root, and body-point control within the same formulation. In benchmark evaluations, AnchorRoute outperforms prior sparse-control methods under the sparse keyjoint protocol and consistently improves anchor adherence across control families. The results show that the learned anchor-conditioned generator and RouteSolver refinement are complementary: the generator preserves text-motion quality, while RouteSolver provides a controllable path toward stronger anchor adherence.

翻译：稀疏锚点为人机运动创作提供了紧凑的交互接口：用户仅需指定少量根位置、平面轨迹采样点或身体点目标，系统即可合成完整人体运动以补全未充分明确的意图。本文提出AnchorRoute框架——一种基于稀疏锚点的运动合成框架，该框架将锚点作为生成与精化的共享基座。在生成阶段，AnchorRoute将稀疏锚点转化为锚点条件特征，通过AnchorKV与双上下文条件注入机制，将所得条件记忆注入冻结的过渡掩码扩散先验模型。该方法在保留预训练文本转运动先验模型生成质量的同时，习得稀疏空间控制能力。生成完成后，同一组锚点被评估为残差：其时间戳定义精化区间，残差值决定需重点修正的位置。RouteSolver通过将软令牌更新投影至锚点定义的分段仿射区间基实现运动精化。这种设计在单一锚点基座框架下，将生成阶段的锚点条件控制与残差路由精化相耦合。AnchorRoute支持根三维控制、平面根控制及身体点控制，均采用统一公式。基准评估表明，在稀疏关键关节协议下，AnchorRoute优于现有稀疏控制方法，并在各类控制族中持续提升锚点遵从度。实验结果显示，习得的锚点条件生成器与RouteSolver精化机制具有互补性：生成器保持文本运动质量，而RouteSolver提供通向更强锚点遵从性的可控路径。