Sketching is a natural and effective visual communication medium commonly used in creative processes. Recent developments in deep-learning models drastically improved machines' ability in understanding and generating visual content. An exciting area of development explores deep-learning approaches used to model human sketches, opening opportunities for creative applications. This chapter describes three fundamental steps in developing deep-learning-driven creativity support tools that consumes and generates sketches: 1) a data collection effort that generated a new paired dataset between sketches and mobile user interfaces; 2) a sketch-based user interface retrieval system adapted from state-of-the-art computer vision techniques; and, 3) a conversational sketching system that supports the novel interaction of a natural-language-based sketch/critique authoring process. In this chapter, we survey relevant prior work in both the deep-learning and human-computer-interaction communities, document the data collection process and the systems' architectures in detail, present qualitative and quantitative results, and paint the landscape of several future research directions in this exciting area.
翻译:深造模型的最新发展极大地提高了机器理解和生成视觉内容的能力。 一个令人振奋的发展领域探索了用于模拟人类素描的深造方法,为创造性应用开辟了机会。本章描述了开发深学习驱动的消费和生成素描的创造性支持工具的三个基本步骤:1)数据收集工作,在素描和移动用户界面之间产生了一个新的对齐数据集;2)基于素描的用户界面检索系统,根据最新计算机视觉技术加以调整;3)谈话素描系统,支持基于自然语言的素描/精细写过程的新的互动。在本章中,我们调查深造和人类计算机互动社区先前的相关工作,详细记录数据收集进程和系统结构,介绍质量和数量结果,并描绘这一令人兴奋领域若干未来研究方向的轮廓。