NeurIPS Workshop in Machine Learning for Creativity and Design
In home decoration, an artwork with a particular combination of colors can convey a positive mood that improves psychological health. In our work, we leverage emotion to color mapping techniques and Generative Adversarial Networks (GANs) to generate artwork that brings a room into a more positive mood. We create a unique workflow to extract the color scheme from a room photo, convert it to an image with target colors that represent the desired positive mood, and then use a conditional GAN to generate artwork with fine control of the color. In this paper, we share our emotion to color mapping pipeline, GAN model training, and evaluation results on the generated artworks.
Donglai Xiang, Timur Bagautdinov, Tuur Stuyck, Fabian Prada, Javier Romero, Weipeng Xu, Shunsuke Saito, Jingfan Guo, Breannan Smith, Takaaki Shiratori, Yaser Sheikh, Jessica Hodgins, Chenglei Wu
Ludwig Sidenmark, Mark Parent, Chi-Hao Wu, Joannes Chan, Michael Glueck, Daniel Wigdor, Tovi Grossman, Marcello Giordano
Simon Vandenhende, Dhruv Mahajan, Filip Radenovic, Deepti Ghadiyaram
