by Steve DiPaola, Graeme McCaig, Nilay Ozge Yalcin, Suk Kyoung Choi

Deep Learning AI Creativity for Visuals / Words


About :: The Research :: Setup and Results :: Downloads and Links :: Contact


About
Using Cognitive Science as a basis for our work, we attempt to model aspects of human creativity in AI. Specially we are using Neural Networks (and evolutionary systems) in the form of Deep Learning, CNNs, RNNs and other modern techniques to model aspects of human expression and creativity. We are known for modelling expression semantics and generation of visual art (stills, videos, VR) but have extended our work into expressive forms of linguistic (word based) narrative.
For a quick over view of the finding see google photo's ALBUM. Or the video work at DiPaola's youtube. For additinal info and images see Downloads and Links.







The Research
See Papers and Videos.

Setup and Results
See Papers and Videos.

Downloads and Links


Papers / Posters
  PDF: ICCC paper PDF: Deep Convolutional Networks as Models of Generalization and Blending Within Visual Creativity
  PDF: EVA Paper PDF: Using Artificial Intelligence Techniques to Emulate the Creativity of a Portrait Painter
  PDF: Journal Paper PDF: Using a Contextual Focus Model for an AutomaticCreativity Algorithm to Generate Art Work

Additional Image and Video Galleries
  Image Repository Repository of Many AI Still Images
  Deep AI Video Texture and Flow - Art Video
  Additional Video AI Stills Creativity Stills using Artifical Intelligence from Movie
    Additional Stills Deep Learning Art Stills.

Contacts:

Steve DiPaola :: sdipaola @ sfu.ca
cell phone (Vancouver, BC) 604.719.6579