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 sequential goal-reaching tasks and confirming its readiness for demanding interactive applications.
COMET can be utilized for various goal-reaching tasks by freely specifying any combination of learned joints (pelvis and the five end-effectors).
1 Joint Control
2 Joints Control
3 Joints Control
6 Joints Control
Since COMET supports multi-joint control, it can be naturally extended from the multi-joint goal-reaching task to handle motion in-betweening.
COMET can stylize the motion by generating a reference for a specific style and applying reference-guided feedback.
Walk Style
Aeroplane Style
Dinosaur Style
Arms Above Hand Style
Bent Forward Style
With RGF enabled, COMET maintains coherent trajectories while accurately reaching all sequential targets.
W/O Reference-guided Feedback
W/ Reference-guided Feedback
The CondMDI and DNO models were reproduced and trained on the AMASS and CIRCLE datasets. All three models do not include any post-processing stage.
CondMDI
DNO
COMET
Left : CondMDI, Middle : DNO, Right : COMET
The SMooDi model was reproduced and trained on the AMASS and CIRCLE datasets.
SMooDi - LeanBack Style
COMET - LeanBack Style