We present a neural network architecture to predict a point in color space from the sequence of characters in the color's name. Using large scale color--name pairs obtained from an online color design forum, we evaluate our model on a "color Turing test" and find that, given a name, the colors predicted by our model are preferred by annotators to color names created by humans. Our datasets and demo system are available online at colorlab.us.
Cite
@article{arxiv.1609.08777,
title = {Character Sequence Models for ColorfulWords},
author = {Kazuya Kawakami and Chris Dyer and Bryan R. Routledge and Noah A. Smith},
journal= {arXiv preprint arXiv:1609.08777},
year = {2016}
}