UniMate: One Unified Model to Animate Diverse Skeletons

TL;DR - UniMate is a topology-aware diffusion transformer that generates text-guided motion for arbitrary rigged 3D skeletons without per-skeleton retraining or test-time optimization. It aims to remove topology-specific constraints from learned animation and enable zero-shot motion transfer across diverse asset types.

• Encodes skeletal structure through graph-aware attention biases, graph-Laplacian spectral rotary embeddings, and a global rest-pose topology conditioner.
• Trains on UniML3D, a curated dataset of 13,006 text-paired motion sequences spanning animals, articulated objects, and varied skeletal topologies.
• Reportedly outperforms existing baselines in motion quality, generalization, and efficiency.
• Supports zero-shot cross-topology transfer, motion in-betweening and expansion, and text-guided editing.