Culture-inspired Multi-modal Color Palette Generation and Colorization: A Chinese Youth Subculture Case

Authors: Yufan Li, Jinggang Zhuo, Ling Fan, Harry Jiannan Wang

accepted by the 3rd IEEE Workshop on Artificial Intelligence for Art Creation
License: CC BY 4.0

Abstract: Color is an essential component of graphic design, acting not only as a visual factor but also carrying cultural implications. However, existing research on algorithmic color palette generation and colorization largely ignores the cultural aspect. In this paper, we contribute to this line of research by first constructing a unique color dataset inspired by a specific culture, i.e., Chinese Youth Subculture (CYS), which is an vibrant and trending cultural group especially for the Gen Z population. We show that the colors used in CYS have special aesthetic and semantic characteristics that are different from generic color theory. We then develop an interactive multi-modal generative framework to create CYS-styled color palettes, which can be used to put a CYS twist on images using our automatic colorization model. Our framework is illustrated via a demo system designed with the human-in-the-loop principle that constantly provides feedback to our algorithms. User studies are also conducted to evaluate our generation results.

Submitted to arXiv on 10 Feb. 2021

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