UniMate: One Unified Model to Animate Diverse Skeletons
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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.
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UniMate: One Unified Model to Animate Diverse Skeletons
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Hugging Face upvotes 16
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.