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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