Global Physical Prior Based Fluid Reconstruction for VR/AR

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Fluid is a common natural phenomenon and often appears in various VR/AR applications. Several works use sparse view images and integrate physical priors to improve reconstruction results. However, existing works only consider physical priors between adjacent frames. In our work, we propose a differentiable fluid simulator combined with a differentiable renderer for fluid reconstruction, which can make full use of global physical priors among long series. Furthermore, we introduce divergence-free Laplacian eigenfunctions as velocity bases to improve efficiency and save memory. We demonstrate our method on both synthetic and real data and show that it can produce better results.

Original languageEnglish
Title of host publicationProceedings - 2023 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages823-824
Number of pages2
ISBN (Electronic)9798350348392
DOIs
StatePublished - 2023
Event2023 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2023 - Shanghai, China
Duration: 25 Mar 202329 Mar 2023

Publication series

NameProceedings - 2023 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2023

Conference

Conference2023 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2023
Country/TerritoryChina
CityShanghai
Period25/03/2329/03/23

Keywords

  • Computing methodologies
  • Model development and analysis
  • Modeling and simulation
  • Modeling methodologies

Fingerprint

Dive into the research topics of 'Global Physical Prior Based Fluid Reconstruction for VR/AR'. Together they form a unique fingerprint.

Cite this