Xu Peng, Hospedales Timothy M, Yin Qiyue, Song Yi-Zhe, Xiang Tao, Wang Liang
IEEE Trans Pattern Anal Mach Intell. 2023 Jan;45(1):285-312. doi: 10.1109/TPAMI.2022.3148853. Epub 2022 Dec 5.
Free-hand sketches are highly illustrative, and have been widely used by humans to depict objects or stories from ancient times to the present. The recent prevalence of touchscreen devices has made sketch creation a much easier task than ever and consequently made sketch-oriented applications increasingly popular. The progress of deep learning has immensely benefited free-hand sketch research and applications. This paper presents a comprehensive survey of the deep learning techniques oriented at free-hand sketch data, and the applications that they enable. The main contents of this survey include: (i) A discussion of the intrinsic traits and unique challenges of free-hand sketch, to highlight the essential differences between sketch data and other data modalities, e.g., natural photos. (ii) A review of the developments of free-hand sketch research in the deep learning era, by surveying existing datasets, research topics, and the state-of-the-art methods through a detailed taxonomy and experimental evaluation. (iii) Promotion of future work via a discussion of bottlenecks, open problems, and potential research directions for the community.
手绘草图具有很强的说明性，从古至今一直被人类广泛用于描绘物体或讲述故事。近年来，触摸屏设备的普及使草图创作比以往任何时候都更加轻松，从而使面向草图的应用程序越来越受欢迎。深度学习的发展极大地推动了手绘草图的研究与应用。本文对面向手绘草图数据的深度学习技术及其所支持的应用进行了全面综述。本综述的主要内容包括：（i）对手绘草图的内在特征和独特挑战进行讨论，以突出草图数据与其他数据模态（如自然照片）之间的本质区别。（ii）通过详细的分类法和实验评估，对现有数据集、研究主题和当前最先进的方法进行调研，回顾深度学习时代手绘草图研究的发展历程。（iii）通过讨论该领域的瓶颈、开放性问题和潜在研究方向，对未来工作进行展望。
