83 citations · 140 across the 5 of their papers we have counts for
3 papers · 1 filter
Lagrangian Neural Style Transfer for Fluids
Byungsoo Kim, Vinicius C. Azevedo, Markus Gross +1
Artistically controlling the shape, motion and appearance of fluid simulations pose major challenges in visual effects production. In this paper, we present a neural style transfer…
Data-Driven Physical Face Inversion
Yeara Kozlov, Hongyi Xu, Moritz Bächer +3
Facial animation is one of the most challenging problems in computer graphics, and it is often solved using linear heuristics like blend-shape rigging. More expressive approaches l…
Transport-Based Neural Style Transfer for Smoke Simulations
Byungsoo Kim, Vinicius C. Azevedo, Markus Gross +1
Artistically controlling fluids has always been a challenging task. Optimization techniques rely on approximating simulation states towards target velocity or density field configu…