English

Controllable Long-term Motion Generation with Extended Joint Targets

Computer Vision and Pattern Recognition 2025-12-05 v1

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.

Keywords

Cite

@article{arxiv.2512.04487,
  title  = {Controllable Long-term Motion Generation with Extended Joint Targets},
  author = {Eunjong Lee and Eunhee Kim and Sanghoon Hong and Eunho Jung and Jihoon Kim},
  journal= {arXiv preprint arXiv:2512.04487},
  year   = {2025}
}

Comments

WACV 2026

R2 v1 2026-07-01T08:08:55.354Z