ClusterStyle: Modeling Intra-Style Diversity with Prototypical Clustering for Stylized Motion Generation

• URL: http://arxiv.org/abs/2512.02453v1
• Date: Tue, 02 Dec 2025 06:24:14 GMT
• Title: ClusterStyle: Modeling Intra-Style Diversity with Prototypical Clustering for Stylized Motion Generation
• Authors: Kerui Chen, Jianrong Zhang, Ming Li, Zhonglong Zheng, Hehe Fan,
• Abstract summary: We propose a clustering-based framework, ClusterStyle, to address intra-style diversity.<n>We leverage a set of prototypes to model diverse style patterns across motions belonging to the same style category.<n>Our approach outperforms existing state-of-the-art models in stylized motion generation and motion style transfer.
• Score: 33.75564496181951
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Existing stylized motion generation models have shown their remarkable ability to understand specific style information from the style motion, and insert it into the content motion. However, capturing intra-style diversity, where a single style should correspond to diverse motion variations, remains a significant challenge. In this paper, we propose a clustering-based framework, ClusterStyle, to address this limitation. Instead of learning an unstructured embedding from each style motion, we leverage a set of prototypes to effectively model diverse style patterns across motions belonging to the same style category. We consider two types of style diversity: global-level diversity among style motions of the same category, and local-level diversity within the temporal dynamics of motion sequences. These components jointly shape two structured style embedding spaces, i.e., global and local, optimized via alignment with non-learnable prototype anchors. Furthermore, we augment the pretrained text-to-motion generation model with the Stylistic Modulation Adapter (SMA) to integrate the style features. Extensive experiments demonstrate that our approach outperforms existing state-of-the-art models in stylized motion generation and motion style transfer.

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