馃殌 Excited to share our new paper:
"DynTex: A real-time generative model of dynamic naturalistic luminance textures"
...now published in Journal of Vision!
馃敼 Why it matters: Dynamic textures (e.g., fire, water, foliage) are everywhere, but modeling them in real-time has been a challenge. DynTex bridges this gap with a biologically inspired, efficient approach.
馃敼 Key innovation: A generative model that captures the spatiotemporal statistics of natural scenes while running in real-time.
馃敼 Applications: Computer vision, neuroscience, VR/AR, and more.馃摉
Read it here: https://doi.org/10.1167/jov.25.11.2
with Andrew Meso, Nikos Gekas, Jonathan Vacher, Pascal Mamassian and Guillaume Masson
More on: https://laurentperrinet.github.io/publication/meso-25/
#DynamicTextures#ComputationalNeuroscience#ComputerVision#GenerativeModels#OpenScience