Character Sequence Models for ColorfulWords
This work addresses a domain-specific problem in color design, offering an incremental improvement in automated color prediction.
The paper tackles the problem of predicting colors from color names using a neural network architecture, achieving a result where model-generated colors are preferred over human-created ones in a 'color Turing test'.
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.