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cs.GR2026
ARDY: Autoregressive Diffusion with Hybrid Representation for Interactive Human Motion Generation
Kaifeng Zhao, Mathis Petrovich, Haotian Zhang +3
Generating realistic 3D human motions in real-time within interactive applications is key for animation, simulation, and humanoid robotics. While recent offline motion generation a…
cs.RO2026
MotionBricks: Scalable Real-Time Motions with Modular Latent Generative Model and Smart Primitives
Tingwu Wang, Olivier Dionne, Michael De Ruyter +13
Despite transformative advances in generative motion synthesis, real-time interactive motion control remains dominated by traditional techniques. In this work, we identify two key…
cs.CV2026
Kimodo: Scaling Controllable Human Motion Generation
Davis Rempe, Mathis Petrovich, Ye Yuan +21
High-quality human motion data is becoming increasingly important for applications in robotics, simulation, and entertainment. Recent generative models offer a potential data sourc…