Deep Learning-Based Motion Style Transfer Tools, Techniques and Future Challenges

Deep Learning-Based Motion Style Transfer Tools, Techniques and Future Challenges

In the fourth industrial revolution, the scale of execution for interactive applications increased substantially. These interactive and animated applications are human-centric, and the representation of human motion is unavoidable, making the representation of human motions ubiquitous. Animators str...

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Bibliographic Details
Main Authors: Syed Muhammad Abrar Akber, Sadia Nishat Kazmi, Syed Muhammad Mohsin, Agnieszka Szczęsna
Format: Article
Language:English
Published: MDPI AG 2023-02-01
Series:Sensors
Subjects:
deep learning
deep neural networks
human motions
motions style transfer
motion datasets
Online Access:https://www.mdpi.com/1424-8220/23/5/2597

Internet

https://www.mdpi.com/1424-8220/23/5/2597

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