humanoid-gpt-scaling-data-and-structure-for-zero-shot-motion-tracking-232090a3·1 events·first seen Aliases: Humanoid-GPT: Scaling Data and Structure for Zero-Shot Motion Tracking
Researchers introduce Humanoid-GPT, a causal Transformer pre-trained on a 2-billion-frame retargeted motion corpus that unifies major mocap datasets with large-scale in-house recordings for whole-body humanoid control. The model achieves zero-shot generalization to unseen motions and control tasks, overcoming the agility-generalization trade-off seen in prior MLP-based trackers. Scaling analyses demonstrate a new performance frontier for dynamic motion tracking without task-specific fine-tuning.