让任意骨骼动起来：通用动作编码器突破物种限制
NECromancer: Breathing Life into Skeletons via BVH Animation
- 基于BVH文件的结构先验，构建通用骨骼嵌入
- 实现跨物种动作压缩与高保真重建，压缩率超10倍
- 支持跨物种动作迁移、生成与文本检索，适合动画开发
动作标记化是通用动作模型的关键，但现有方法多局限于特定物种骨骼，难以适配多样形态。本文提出NECromancer（NEC），一种直接作用于任意BVH骨骼的通用动作标记器。其由三部分组成：(1) 语义感知骨骼图编码器（OwO），从BVH文件中提取关节语义、静止姿态偏移和骨骼拓扑等结构先验；(2) 拓扑无关标记器（TAT），将动作序列压缩为统一、拓扑不变的离散表示；(3) 统一BVH宇宙（UvU），一个大规模跨异构骨骼的动作数据集。实验表明，NEC在显著压缩下实现高保真重建，并有效解耦动作与骨骼结构。所获标记空间支持跨物种动作迁移、组合、去噪、基于标记的生成及文本-动作检索，建立跨形态动作分析与合成的统一框架。
原文摘要 · Abstract (English)
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/
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