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Machine learning based co-creative design framework

23 January 2020
Brian Quanz
Wei-Ling Sun
Ajay A. Deshpande
Dhruv Shah
Jae-eun Park
    HAI
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Abstract

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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