Search Results for author: Christian Mandery

Found 2 papers, 1 papers with code

Learning a bidirectional mapping between human whole-body motion and natural language using deep recurrent neural networks

no code implementations18 May 2017 Matthias Plappert, Christian Mandery, Tamim Asfour

We evaluate our approach on 2, 846 human whole-body motions and 6, 187 natural language descriptions thereof from the KIT Motion-Language Dataset.

Feature Engineering Machine Translation

The KIT Motion-Language Dataset

1 code implementation13 Jul 2016 Matthias Plappert, Christian Mandery, Tamim Asfour

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.

Cannot find the paper you are looking for? You can Submit a new open access paper.