Deep Learning for Identifying Potential Conceptual Shifts for Co-creative Drawing

Karimi, Pegah, Davis, Nicholas, Grace, Kazjon, Maher, Mary Lou

arXiv.org Machine Learning 

We present a system for identifying conceptual shifts between visual categories, which will form the basis for a co-creative drawing system to help users draw more creative sketches. The system recognizes human sketches and matches them to structurally similar sketches from categories to which they do not belong. This would allow a co-creative drawing system to produce an ambiguous sketch that blends features from both categories.

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