Real-time Animation Generation and Control on Rigged Models via Large Language Models
CoRR(2023)
摘要
We introduce a novel method for real-time animation control and generation on
rigged models using natural language input. First, we embed a large language
model (LLM) in Unity to output structured texts that can be parsed into diverse
and realistic animations. Second, we illustrate LLM's potential to enable
flexible state transition between existing animations. We showcase the
robustness of our approach through qualitative results on various rigged models
and motions.
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