Machine learning based co-creative design framework

Quanz, Brian, Sun, Wei, Deshpande, Ajay, Shah, Dhruv, Park, Jae-eun

arXiv.org Artificial Intelligence 

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.

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