Hierarchical Cloth Simulation using Deep Neural Networks

Fast and reliable physically-based simulation techniques are essential for providing flexible visual effects for computer graphics content. In this paper, we propose a fast and reliable hierarchical cloth simulation method, which combines conventional physically-based simulation with deep neural net...

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Bibliographic Details
Published inarXiv.org
Main Authors Young Jin Oh, Lee, Tae Min, Lee, In-Kwon
Format Paper
LanguageEnglish
Published Ithaca Cornell University Library, arXiv.org 09.02.2018
Subjects
Cloth
Computer graphics
Computer simulation
Neural networks
Simulation
Visual effects
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Summary:Fast and reliable physically-based simulation techniques are essential for providing flexible visual effects for computer graphics content. In this paper, we propose a fast and reliable hierarchical cloth simulation method, which combines conventional physically-based simulation with deep neural networks (DNN). Simulations of the coarsest level of the hierarchical model are calculated using conventional physically-based simulations, and more detailed levels are generated by inference using DNN models. We demonstrate that our method generates reliable and fast cloth simulation results through experiments under various conditions.
ISSN:2331-8422