Image Diffusion Models Are Good 3D Human Motion Generators
Text-to-motion generation typically relies on dataset-specific skeletal representations, with models trained separately for benchmarks with different joint layouts. We investigate whether image diffusion architectures can model 3D human motion through a common image-compatible representation that accommodates heterogeneous skeletal layouts while preserving motion-specific kinematic structure. To this end, we organize root-centered joint trajectories into topology-informed joint--time images and model global root dynamics through a complementary latent stream. A motion autoencoder conditions local-motion decoding on the root latent, while a text-conditioned Scalable Interpolant Transformer...
| Authors | Siyuan Yang, Chong Wang, Hao Cheng et al. |
|---|---|
| Primary category | cs.CV |
| Published | 9 October 2026 |
| Last updated at source | 9 October 2026 |
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