We present a novel approach named OmniControl for incorporating flexible spatial control signals into a text-conditioned human motion generation model based on the diffusion process. Unlike previous methods that can only control the pelvis trajectory, OmniControl can incorporate flexible spatial control signals over different joints at different times with only one model. Specifically, we propose analytic spatial guidance that ensures the generated motion can tightly conform to the input control signals. At the same time, realism guidance is introduced to refine all the joints to generate more coherent motion. Both the spatial and realism guidance are essential and they are highly complementary for balancing control accuracy and motion realism. By combining them, OmniControl generates motions that are realistic, coherent, and consistent with the spatial constraints. Experiments on HumanML3D and KIT-ML datasets show that OmniControl not only achieves significant improvement over state-of-the-art methods on pelvis control but also shows promising results when incorporating the constraints over other joints.

翻译：我们提出了一种名为 OmniControl 的新型方法，用于将灵活的空间控制信号整合到基于扩散过程的文本条件人体运动生成模型中。与以往仅能控制骨盆轨迹的方法不同，OmniControl 仅需单一模型即可在不同时刻对不同关节施加灵活的空间控制信号。具体而言，我们提出解析空间引导机制，确保生成的运动与输入控制信号紧密吻合；同时引入真实感引导机制，优化所有关节以生成更连贯的运动。空间引导与真实感引导均至关重要，二者高度互补，可在控制精度与运动真实感之间取得平衡。通过融合这两种引导机制，OmniControl 能够生成既真实连贯又符合空间约束的运动。在 HumanML3D 和 KIT-ML 数据集上的实验表明，OmniControl 不仅在骨盆控制任务上显著超越现有最优方法，而且在其它关节约束任务中也展现出令人期待的结果。