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Exploring Sketch-based Character Design Guided by Automatic Colorization

Rawan Alghofaili (George Mason University), Matthew Fisher (Adobe Research), Richard Zhang (Adobe Research), Michal Lukáč (Adobe Research), Lap-Fai Yu (George Mason University)


Proceedings of Graphics Interface 2021:
Virtual Event,
28 – 29 May 2021, pp. 56 – 67

Abstract

Character design is a lengthy process, requiring artists to iteratively alter their characters' features and colorization schemes according to feedback from creative directors or peers. Artists experiment with multiple colorization schemes before deciding on the right color palette. This process may necessitate several tedious manual re-colorizations of the character. Any substantial changes to the character's appearance may also require manual re-colorization. Such complications motivate a computational approach for visualizing characters and drafting solutions. We propose a character exploration tool that automatically colors a sketch based on a selected style. The tool employs a Generative Adversarial Network trained to automatically color sketches. The tool also allows a selection of faces to be used as a template for the character's design. We validated our tool by comparing it with using Photoshop for character exploration in our pilot study. Finally, we conducted a study to evaluate our tool's efficacy within the design pipeline.

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