Machine learning based co-creative design framework
Brian Quanz, Wei Sun, Ajay Deshpande, Dhruv Shah, Park, Jae-eun · arXiv (Cornell University) · 2020
We propose a flexible, co-creative framework bringing together multiple machine learning techniques to assist human users to efficiently produce effective creative designs. We demonstrate its potential with a perfume bottle design case study, including human evaluation and quantitative and qualitative analyses.