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Found 2 papers, 1 papers with code
Learning a bidirectional mapping between human whole-body motion and natural language using deep recurrent neural networks
We evaluate our approach on 2, 846 human whole-body motions and 6, 187 natural language descriptions thereof from the KIT Motion-Language Dataset.
The KIT Motion-Language Dataset
Linking human motion and natural language is of great interest for the generation of semantic representations of human activities as well as for the generation of robot activities based on natural language input.
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