DeepWarp: DNN-based Nonlinear Deformation

DeepWarp is an efficient and highly re-usable deep neural network (DNN) based nonlinear deformable simulation framework. Unlike other deep learning applications such as image recognition, where different inputs have a uniform and consistent format (e.g. an array of all the pixels in an image), the input for deformable simulation is quite variable, high-dimensional, and parametrization-unfriendly….Read More

tempoGAN: A Temporally Coherent, Volumetric GAN for Super-resolution Fluid Flow

Generative Adversarial Networks (GANs) have been on a tear these last few months, providing rapid advances particularly in the field of realistic image generation. This application to fluids is interesting not only because it extends the architecture into 3D but also for what it allows. It’s long been desired to use low resolution proxy layout…Read More

Accelerating Eulerian Fluid Simulation With Convolutional Networks

When asking those in the VFX industry which processes are the slowest and most compute-intensive fluid simulation is bound to be somewhere towards the top of the list. Physical phenomena such as fire and water are notoriously difficult to control, even in the hands of the most experienced artists, and usually require a significant number…Read More