# ScalarFlow: a large-scale volumetric data set of real-world scalar transport flows for computer animation and machine learning

@article{Eckert2019ScalarFlowAL, title={ScalarFlow: a large-scale volumetric data set of real-world scalar transport flows for computer animation and machine learning}, author={Marie-Lena Eckert and Kiwon Um and Nils Thuerey}, journal={ACM Trans. Graph.}, year={2019}, volume={38}, pages={239:1-239:16} }

In this paper, we present ScalarFlow, a first large-scale data set of reconstructions of real-world smoke plumes. We additionally propose a framework for accurate physics-based reconstructions from a small number of video streams. Central components of our algorithm are a novel estimation of unseen inflow regions and an efficient regularization scheme. Our data set includes a large number of complex and natural buoyancy-driven flows. The flows transition to turbulent flows and contain…

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