Compute-Optimal Scaling Laws for Human Motion Generation Released
andrew_n_carr · x · 2026-08-25
This paper presents compute-optimal scaling laws for human motion generation, addressing the historical data constraints in the field. By building the world's largest, high-quality human-motion dataset and training hundreds of models, the authors prove that scaling significantly improves performance. This holds promise for animators, roboticists, and game developers.
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