Machine learning based co-creative design framework
This addresses the challenge of enhancing efficiency and effectiveness in creative design processes for designers or users, but appears incremental as it combines existing techniques.
The authors tackled the problem of assisting human users in creative design by proposing a co-creative framework that integrates multiple machine learning techniques, demonstrated through a perfume bottle design case study with human evaluation and analyses.
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.