SOURCE-LINKED INTELLIGENCE
UniMate: One Unified Model to Animate Diverse Skeletons
Recent advances in automatic rigging now deliver animation-ready 3D assets at scale, yet generating the motion to drive them remains a bottleneck. Existing learned animators are topology-constrained: they rely on category-specific templates or require per-skeleton fine-tuning and reference motions at inference. We present UniMate, a unified foundation model that synthesizes articulated motion for arbitrary skeletons from a rigged 3D asset and a text prompt, with no test-time optimization or per-skeleton retraining. UniMate introduces a topology-aware diffusion transformer, which integrates ske
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-04T17:59:00.000Z
First collected: 2026-09-20T21:52:07.471Z. This is not the publication date.