Artistically controlling fluids has always been a challenging task. Recently, volumetric Neural
Style Transfer (NST) techniques have been used to artistically manipulate smoke simulation …

Three-dimensional cloud retrievals are critical for understanding their impact on climate and
other applications, such as aviation safety, weather prediction, and remote sensing …

The dynamic effects of smoke are impressive in illustration design, but it is a troublesome
and challenging issue for inexpert users to design smoke effects without domain knowledge …

Volumetric phenomena, such as clouds and fog, present a significant challenge for 3D
reconstruction systems due to their translucent nature and their complex interactions with …

Controlling fluid simulations is notoriously difficult due to its high computational cost and the
fact that user control inputs can cause unphysical motion. We present an interactive method …

Physics-based fluid control has long been a challenging problem in balancing efficiency and
accuracy. We introduce a novel physics-based fluid control pipeline using Laplacian …

This book is an introduction to the use of machine learning and data-driven approaches in
fluid simulation and animation, as an alternative to traditional modeling techniques based on …

This study evaluates deep-learning and Shape from Silhouette (SfS) methods for 3D
reconstruction of smoke plumes. It demonstrates the deep-learning method's superiority in …

The design of heating, ventilation and air conditioning smoke control and exhaust is a
complex and comprehensive engineering system, which covers all elements inside and …

In this chapter, we consider perspectives in deep learning for fluid animation. Firstly, the
input data generation for neural network training depends on simulating fluid dynamics …