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Hierarchical Cloth Simulation using Deep Neural Networks

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Citation:
Young Jin Oh, Tae Min Lee, and In-Kwon Lee, "Hierarchical Cloth Simulation using Deep Neural Networks", Proceedings of Computer Graphics International (CGI) 2018, June 2018
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Abstract:
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.
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