Efficient Generation of Multimodal Fluid Simulation Data
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Date
2024
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
In this work, we introduce an efficient and intuitive framework to produce synthetic multi-modal datasets of fluid simulations. The proposed pipeline can reproduce the dynamics of fluid flows and allows for exploring and learning various properties of their complex behavior from distinct perspectives and modalities. We aim to exploit these properties to fulfill the community's need for standardized training data, fostering more reproducible and robust research. We employ our framework to generate a set of thoughtfully designed training datasets, which attempt to span specific fluid simulation scenarios meaningfully. We demonstrate the properties of our contributions by evaluating recently published algorithms for the neural fluid simulation and fluid inverse rendering tasks using our benchmark datasets.
Description
CCS Concepts: Computing methodologies → Physical simulation; Computer graphics
@inproceedings{10.2312:stag.20241332,
booktitle = {Smart Tools and Applications in Graphics - Eurographics Italian Chapter Conference},
editor = {Caputo, Ariel and Garro, Valeria and Giachetti, Andrea and Castellani, Umberto and Dulecha, Tinsae Gebrechristos},
title = {{Efficient Generation of Multimodal Fluid Simulation Data}},
author = {Baieri, Daniele and Crisostomi, Donato and Esposito, Stefano and Maggioli, Filippo and Rodolà, Emanuele},
year = {2024},
publisher = {The Eurographics Association},
ISSN = {2617-4855},
ISBN = {978-3-03868-265-3},
DOI = {10.2312/stag.20241332}
}