ARDY: Autoregressive Diffusion with Hybrid Representation for Interactive Human Motion Generation
Generating realistic 3D human motions in real-time within interactive applications is key for animation, simulation, and humanoid robotics. While recent offline motion generation approaches offer precise control via text and kinematic constraints, they lack the inference speed required for interactive settings. Conversely, existing online methods enable real-time synthesis but often sacrifice controllability or struggle with complex text semantics and long-horizon goals due to limited context windows. In this work, we introduce ARDY, a streaming generation framework that bridges this gap by enabling high-fidelity motion generation controllable via online text prompts and flexible kinemati...
| Authors | Kaifeng Zhao, Mathis Petrovich, Haotian Zhang et al. |
|---|---|
| Primary category | cs.GR |
| Published | 9 July 2026 |
| Last updated at source | 9 July 2026 |
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