Real-time Animation Generation and Control on Rigged Models via Large Language Models
Han Huang ⋅ Fernanda De La Torre ⋅ Cathy Mengying Fang ⋅ Andrzej Banburski ⋅ Judith Amores ⋅ Jaron Lanier
2023 Spotlight
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Workshop: NeurIPS 2023 Workshop on Machine Learning for Creativity and Design
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Workshop: NeurIPS 2023 Workshop on Machine Learning for Creativity and Design
Abstract
We introduce a novel method for real-time animation control and generation onrigged models using natural language input. First, we embed a large languagemodel (LLM) in Unity to output structured texts that can be parsed into diverseand realistic animations. Second, we illustrate LLM’s potential to enable flexiblestate transition between existing animations. We showcase the robustness of ourapproach through qualitative results on various rigged models and motions.
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