no code implementations • 6 Mar 2024 • Francisco Ibarrola, Kazjon Grace
Quality and diversity have been proposed as reasonable heuristics for assessing content generated by co-creative systems, but to date there has been little agreement around what constitutes the latter or how to measure it.
1 code implementation • 20 Feb 2023 • Francisco Ibarrola, Rohan Lulham, Kazjon Grace
In creativity support and computational co-creativity contexts, the task of discovering appropriate prompts for use with text-to-image generative models remains difficult.
no code implementations • 24 Jun 2019 • Pegah Karimi, Mary Lou Maher, Nicholas Davis, Kazjon Grace
This paper presents a computational model for conceptual shifts, based on a novelty metric applied to a vector representation generated through deep learning.
no code implementations • 25 Jul 2018 • Pegah Karimi, Kazjon Grace, Mary Lou Maher, Nicholas Davis
This paper provides a framework for evaluating creativity in co-creative systems: those that involve computer programs collaborating with human users on creative tasks.
no code implementations • 2 Jan 2018 • Pegah Karimi, Nicholas Davis, Kazjon Grace, Mary Lou Maher
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.