SpecTrHuMS: Spectral transformer for human mesh sequence learning

We present SpecTrHuMS, a Spectral Transformer for 3D triangular Human Mesh Sequence learning which combines known deep learning models with spectral mesh processing to capture characteristics of 3D shapes as well as temporal dependencies between the frames. Unlike previous works in this field, our a...

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Veröffentlicht in:	Computers & graphics Jg. 115; S. 191 - 203
Hauptverfasser:	Lemeunier, Clément, Denis, Florence, Lavoué, Guillaume, Dupont, Florent
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 01.10.2023 Elsevier
Schlagworte:	Autoencoder Computer Science Computer Vision and Pattern Recognition Geometric deep learning Human body triangular mesh sequences Machine Learning Spectral analysis Transformers Transformers Geometric deep learning Autoencoder Human body triangular mesh sequences Spectral analysis Geometric Deep Learning
ISSN:	0097-8493
Online-Zugang:	Volltext
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