How does a young child learn that a plush toy, a crude drawing, and a photograph are all distinct representations of the same content, such as a bear? Embedded in this question is a requirement to disentangle the content of visual input from its form of delivery. These concerns are important to many domains, including computer vision and the creation of visual culture. This project considers the problem of formalizing the concepts of ‘style’ and ‘content’ in images and video. Despite their importance, and our intuitive understanding of these distinctions, there are no compelling and technically useful definitions of these concepts. The researchers will investigate possible ways to define them and operationalize these definitions to improve the state of the art in style transfer and image analysis, as well as produce novel AI-driven visual artifacts.
Discovery Grant
Disentangling Visual Style and Content
New style transfer models that separate, capture, and manipulate content and style, unlocking potential for art and science.
