Application of Graph Convolutions in a Lightweight Model for Skeletal Human Motion Forecasting

Hermes L, Hammer B, Schilling M (2021)
In: ESANN 2021 proceedings, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. . 111-116.

Konferenzbeitrag | Englisch
 
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Abstract / Bemerkung
Prediction of movements is essential for successful cooperation with intelligent systems. We propose a model that integrates organized spatial information as given through the moving body's skeletal structure. This inherent structure is exploited in our model through application of Graph Convolutions and we demonstrate how this allows leveraging the structured spatial information into competitive predictions that are based on a lightweight model that requires a comparatively small number of parameters.
Erscheinungsjahr
2021
Titel des Konferenzbandes
ESANN 2021 proceedings, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning.
Seite(n)
111-116
Page URI
https://pub.uni-bielefeld.de/record/2958664

Zitieren

Hermes L, Hammer B, Schilling M. Application of Graph Convolutions in a Lightweight Model for Skeletal Human Motion Forecasting. In: ESANN 2021 proceedings, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. . 2021: 111-116.
Hermes, L., Hammer, B., & Schilling, M. (2021). Application of Graph Convolutions in a Lightweight Model for Skeletal Human Motion Forecasting. ESANN 2021 proceedings, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. , 111-116.
Hermes, L., Hammer, B., and Schilling, M. (2021). “Application of Graph Convolutions in a Lightweight Model for Skeletal Human Motion Forecasting” in ESANN 2021 proceedings, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. 111-116.
Hermes, L., Hammer, B., & Schilling, M., 2021. Application of Graph Convolutions in a Lightweight Model for Skeletal Human Motion Forecasting. In ESANN 2021 proceedings, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. . pp. 111-116.
L. Hermes, B. Hammer, and M. Schilling, “Application of Graph Convolutions in a Lightweight Model for Skeletal Human Motion Forecasting”, ESANN 2021 proceedings, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. , 2021, pp.111-116.
Hermes, L., Hammer, B., Schilling, M.: Application of Graph Convolutions in a Lightweight Model for Skeletal Human Motion Forecasting. ESANN 2021 proceedings, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. . p. 111-116. (2021).
Hermes, Luca, Hammer, Barbara, and Schilling, Malte. “Application of Graph Convolutions in a Lightweight Model for Skeletal Human Motion Forecasting”. ESANN 2021 proceedings, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. . 2021. 111-116.

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arXiv: 2110.04810

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