TY - GEN
T1 - Hierarchical cloth simulation using deep neural networks
AU - Oh, Young Jin
AU - Lee, Tae Min
AU - Lee, In Kwon
N1 - Publisher Copyright:
© 2018 ACM.
Copyright:
Copyright 2019 Elsevier B.V., All rights reserved.
PY - 2018/6/11
Y1 - 2018/6/11
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85062870738&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85062870738&partnerID=8YFLogxK
U2 - 10.1145/3208159.3208162
DO - 10.1145/3208159.3208162
M3 - Conference contribution
AN - SCOPUS:85062870738
T3 - ACM International Conference Proceeding Series
SP - 139
EP - 146
BT - Proceedings of Computer Graphics International, CGI 2018
PB - Association for Computing Machinery
T2 - 2018 Computer Graphics International Conference, CGI 2018
Y2 - 11 June 2018 through 14 June 2018
ER -