Abstract
Generating stable and controllable character motion in real-time is a key challenge in computer animation. Existing methods often fail to provide fine-grained control or suffer from motion degradation over long sequences, limiting their use in interactive applications. We propose COMET, an autoregressive framework that runs in real time, enabling versatile character control and robust long-horizon synthesis. Our efficient Transformer-based conditional VAE allows for precise, interactive control over arbitrary user-specified joints for tasks like goal-reaching and in-betweening from a single model. To ensure long-term temporal stability, we introduce a novel reference-guided feedback mechanism that prevents error accumulation. This mechanism also serves as a plug-and-play stylization module, enabling real-time style transfer. Extensive evaluations demonstrate that COMET robustly generates high-quality motion at real-time speeds, significantly outperforming state-of-the-art approaches in complex motion control tasks and confirming its readiness for demanding interactive applications.
Abstract (translated)
实时生成稳定且可控的角色动画是计算机动画中的一个关键挑战。现有方法往往难以提供精细的控制，或者在长时间序列中会出现动作退化的问题，从而限制了它们在交互式应用程序中的应用。我们提出了COMET（条件变分自编码器框架），这是一个自回归框架，在实时运行时能够实现多样化的角色控制和长期稳定的合成。 我们的高效Transformer基条件VAE模型允许用户对任意指定的关节进行精确、互动式的控制，适用于目标到达和过渡动作等任务，并且仅需一个模型即可完成。为了确保长时间序列中的时间稳定性，我们引入了一种新颖的参考引导反馈机制，以防止错误积累。这一机制还作为插件式的风格化模块存在，能够实现实时风格转换。 广泛的评估表明，COMET能够在实时速度下生成高质量的动作，并在复杂动作控制任务中显著优于现有最先进的方法，确认了它对于苛刻交互式应用的适用性。
URL
https://arxiv.org/abs/2512.04487
