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ACM Multimedia 2025Content: Multimodal Fusion

Leader is Guided: Interactive Motion Generation via Lead-Follow Paradigm and Trajectory Guidance

Runqi Wang, Caoyuan Ma, Jian Zhao 0013, Hanrui Xu, Dongfang Sun, Haoyang Chen, Lin Xiong, Zheng Wang 0007, Xuelong Li 0001

PDF 由论文原始站点提供,PaperCompass 不保存论文文件。DOI 10.1145/3746027.3755438 ↗

摘要

Generating interactive motion from texts has garnered significant attention in recent years. While text inputs offer greater flexibility, in many practical applications, there is a need to controllably impose strict constraints on the motion range or trajectory of virtual characters. However, existing trajectory-based methods are designed for single-actor scenarios and lack support for interactivity in interactive motions. Moreover, text-only methods struggle to accurately convey user-intended trajectories. The distribution shift between training and inference often leads to trajectory deviation and physical interpenetration. To address the questions mentioned, we introduce two key concepts: (1) Lead-Follow Paradigm: Inspired by role allocation in partner dancing, we decompose complex interactive motion tasks into a Lead-Follow paradigm. The leader's path is optimized first, and the follower's motion is subsequently adjusted for coherence and alignment. (2) Trajectory Guidance: We highlight the pivotal role of 3D trajectory guidance in interactive motion generation and accurately reflect user intentions. Through 3D trajectory control, we can more controllably generate the desired motion while avoiding physical interpenetration. In addition, we further investigate the refinement of motion scopes for interactive agents and propose an effective optimization strategy to enhance motion coherence and controllability. Experimental results show that the proposed approach, by more effectively using trajectory, outperforms existing methods in both realism and accuracy.