Rigel3D: Rig-aware Latents for Animation-Ready 3D Asset Generation
Recent 3D generative models can synthesize high-quality assets, but their outputs are typically static: they lack the skeletal rigs, joint hierarchies, and skinning weights required for animation. This limits their use in games, film, simulation, virtual agents, and embodied AI, where assets must not only look plausible but also move plausibly. We introduce Rigel3D, a generative method for animation-ready 3D assets represented as rigged meshes. Unlike post-hoc auto-rigging methods that attach rigs to completed shapes, our method jointly models geometry and rig structure through coupled surface and skeleton structured latent representations. A rig-aware autoencoder decodes these representa...
| Authors | Nikitas Chatzis, Marios Loizou, Evangelos Kalogerakis |
|---|---|
| Primary category | cs.GR |
| Published | 13 May 2026 |
| Last updated at source | 13 May 2026 |
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