A compositional flow-matching model learns a dictionary of motion primitives with length masks and assembles them via sparse binary placement with geometric continuity losses, reporting SOTA results on two embodied trajectory datasets.
Energymogen: Compositional human motion gen- eration with energy-based diffusion model in latent space
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Sparse Compositional Flow Matching by geometric assembly from motion primitives
A compositional flow-matching model learns a dictionary of motion primitives with length masks and assembles them via sparse binary placement with geometric continuity losses, reporting SOTA results on two embodied trajectory datasets.