Fast Neural Style Transfer for Motion Data

Automating motion style transfer can help save animators time by allowing them to produce a single set of motions, which can then be automatically adapted for use with different characters. The proposed fast, efficient technique for performing neural style transfer of human motion data uses a feed-f...

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Bibliographic Details

Published in:	IEEE computer graphics and applications Vol. 37; no. 4; pp. 42 - 49
Main Authors:	Holden, Daniel, Habibie, Ikhsanul, Kusajima, Ikuo, Komura, Taku
Format:	Magazine Article
Language:	English
Published:	United States IEEE 2017 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Analytical models Animation computer graphics Data models Data transfer (computers) deep learning Human motion machine learning motion capture Motion control Neural networks Optimization style transfer Training Virtual reality
ISSN:	0272-1716, 1558-1756, 1558-1756
Online Access:	Get full text
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