Dynamic Upsampling of Smoke through Dictionary-based Learning

@article{Bai2020DynamicUO,
  title={Dynamic Upsampling of Smoke through Dictionary-based Learning},
  author={Kai-Yi Bai and Wei Li and Mathieu Desbrun and Xiaopei Liu},
  journal={ACM Transactions on Graphics (TOG)},
  year={2020},
  volume={40},
  pages={1 - 19}
}
Simulating turbulent smoke flows with fine details is computationally intensive. For iterative editing or simply faster generation, efficiently upsampling a low-resolution numerical simulation is an attractive alternative. We propose a novel learning approach to the dynamic upsampling of smoke flows based on a training set of flows at coarse and fine resolutions. Our multiscale neural network turns an input coarse animation into a sparse linear combination of small velocity patches present in a… Expand
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