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We present color sails, a discrete-continuous color gamut representation thatextends the color gradient analogy to three dimensions and allows interactivecontrol of the color blending behavior. Our representation models a widevariety of color distributions in a compact manner, and lends itself toapplications such as color exploration for graphic design, illustration andsimilar fields. We propose a Neural Network that can fit a color sail to anyimage. Then, the user can adjust color sail parameters to change the basecolors, their blending behavior and the number of colors, exploring a widerange of options for the original design. In addition, we propose a DeepLearning model that learns to automatically segment an image intocolor-compatible alpha masks, each equipped with its own color sail. Thisallows targeted color exploration by either editing their corresponding colorsails or using standard software packages. Our model is trained on a customdiverse dataset of art and design. We provide both quantitative evaluations,and a user study, demonstrating the effectiveness of color sail interaction.Interactive demos are available at www.colorsails.com.

Color Sails: Discrete-Continuous Palettes for Deep Color Exploration