NECromancer: Breathing Life into Skeletons via BVH Animation
About
Motion tokenization is a key component of generalizable motion models, yet most existing approaches are restricted to species-specific skeletons, limiting their applicability across diverse morphologies. We propose NECromancer (NEC), a universal motion tokenizer that operates directly on arbitrary BVH skeletons. NEC consists of three components: (1) an Ontology-aware Skeletal Graph Encoder (OwO) that encodes structural priors from BVH files, including joint semantics, rest-pose offsets, and skeletal topology, into skeletal embeddings; (2) a Topology-Agnostic Tokenizer (TAT) that compresses motion sequences into a universal, topology-invariant discrete representation; and (3) the Unified BVH Universe (UvU), a large-scale dataset aggregating BVH motions across heterogeneous skeletons. Experiments show that NEC achieves high-fidelity reconstruction under substantial compression and effectively disentangles motion from skeletal structure. The resulting token space supports cross-species motion transfer, composition, denoising, generation with token-based models, and text-motion retrieval, establishing a unified framework for motion analysis and synthesis across diverse morphologies. Demo page: https://animotionlab.github.io/NECromancer/
Related benchmarks
| Task | Dataset | Result | Rank | |
|---|---|---|---|---|
| Motion Reconstruction | HumanML3D (test) | MPJPE0.1084 | 6 | |
| Motion Reconstruction | Objaverse-XL (test) | MPJPE0.0983 | 6 | |
| Motion Reconstruction | Truebones Zoo (test) | MPJPE0.1008 | 6 |