Two-step Temporal Interpolation Network Using Forward Advection for Efficient Smoke Simulation

Young Jin Oh, In Kwon Lee

Research output: Contribution to journalArticlepeer-review

Abstract

In this paper, we propose a two-step temporal interpolation network using forward advection to generate smoke simulation efficiently. By converting a low frame rate smoke simulation computed with a large time step into a high frame rate smoke simulation through inference of temporal interpolation networks, the proposed method can efficiently generate smoke simulation with a high frame rate and low computational costs. The first step of the proposed method is optical flow-based temporal interpolation using deep neural networks (DNNs) for two given smoke animation frames. In the next step, we compute temporary smoke frames with forward advection, a physical computation with a low computational cost. We then interpolate between the results of the forward advection and those of the first step to generate more accurate and enhanced interpolated results. We performed quantitative analyses of the results generated by the proposed method and previous temporal interpolation methods. Furthermore, we experimentally compared the performance of the proposed method with previous methods using DNNs for smoke simulation. We found that the results generated by the proposed method are more accurate and closer to the ground truth smoke simulation than those generated by the previous temporal interpolation methods. We also confirmed that the proposed method generates smoke simulation results more efficiently with lower computational costs than previous smoke simulation methods using DNNs.

Original languageEnglish
Pages (from-to)355-365
Number of pages11
JournalComputer Graphics Forum
Volume40
Issue number2
DOIs
Publication statusPublished - 2021 May

Bibliographical note

Funding Information:
This research was supported by the MSIT (Ministry of Science and ICT), Korea, under the ITRC (Information Technology Research Center) support program (IITP‐2020‐2018‐0‐01419) supervised by the IITP (Institute for Information and Communications Technology Planning and Evaluation) and the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. NRF‐2017R1A2B4005469).

Publisher Copyright:
© 2021 The Author(s) Computer Graphics Forum © 2021 The Eurographics Association and John Wiley & Sons Ltd. Published by John Wiley & Sons Ltd.

All Science Journal Classification (ASJC) codes

  • Computer Graphics and Computer-Aided Design

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