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ARDY introduces a streaming generation framework for real-time, high-fidelity 3D human motion generation controlled by text and kinematic constraints, using a hybrid representation and two-stage autoregressive transformer denoiser.
This paper introduces AnyMo, a unified multimodal framework for human motion generation that combines a Residual FSQ-based motion tokenizer with a scalable masked modeling transformer, along with the OmniHuMo dataset of over 5,000 hours of motion data to enable high-quality synthesis under arbitrary modality combinations.