Efficient learning representation of noise-reduced foam effects with convolutional denoising networks.
This study proposes a neural network framework for modeling the foam effects found in liquid simulation without noise. The position and advection of the foam particles are calculated using the existing screen projection method, and the noise problem that occurs in this process is prevented by using...
Main Authors: | , |
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Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2022-01-01
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Series: | PLoS ONE |
Online Access: | https://doi.org/10.1371/journal.pone.0275117 |