Efficient Cloth Simulation using Miniature Cloth and Upscaling Deep Neural Networks

Cloth simulation requires a fast and stable method for interactively and realistically visualizing fabric materials using computer graphics. We propose an efficient cloth simulation method using miniature cloth simulation and upscaling Deep Neural Networks (DNN). The upscaling DNNs generate the targ...

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Published in:arXiv.org 2019-07
Main Authors: Lee, Tae Min, Young Jin Oh, Lee, In-Kwon
Format: Article
Language:English
Subjects:
Cloth
Computer graphics
Computer simulation
Neural networks
Physical properties
Simulation
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Young Jin Oh
Lee, In-Kwon
description Cloth simulation requires a fast and stable method for interactively and realistically visualizing fabric materials using computer graphics. We propose an efficient cloth simulation method using miniature cloth simulation and upscaling Deep Neural Networks (DNN). The upscaling DNNs generate the target cloth simulation from the results of physically-based simulations of a miniature cloth that has similar physical properties to those of the target cloth. We have verified the utility of the proposed method through experiments, and the results demonstrate that it is possible to generate fast and stable cloth simulations under various conditions.
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subjects Cloth
Computer graphics
Computer simulation
Neural networks
Physical properties
Simulation
title Efficient Cloth Simulation using Miniature Cloth and Upscaling Deep Neural Networks
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