Abstract
We contribute the first large-scale dataset of scene sketches, SketchyScene, with the goal of advancing research on sketch understanding at both the object and scene level. The dataset is created through a novel and carefully designed crowdsourcing pipeline, enabling users to efficiently generate large quantities of realistic and diverse scene sketches. SketchyScene contains more than 29,000 scene-level sketches, 7,000+ pairs of scene templates and photos, and 11,000+ object sketches. All objects in the scene sketches have ground-truth semantic and instance masks. The dataset is also highly scalable and extensible, easily allowing augmenting and/or changing scene composition. We demonstrate the potential impact of SketchyScene by training new computational models for semantic segmentation of scene sketches and showing how the new dataset enables several applications including image retrieval, sketch colorization, editing, and captioning, etc. The dataset and code can be found at https://github.com/SketchyScene/SketchyScene.
Abstract (translated)
我们提供了第一个大型场景草图数据集SketchyScene，目的是在对象和场景层面推进草图理解研究。该数据集是通过一个新颖且精心设计的众包管道创建的，使用户能够有效地生成大量逼真和多样化的场景草图。 SketchyScene包含超过29,000个场景级草图，7,000多对场景模板和照片，以及11,000多个对象草图。场景草图中的所有对象都具有地面实况语义和实例掩码。该数据集还具有高度可扩展性和可扩展性，可轻松实现增强和/或改变场景组合。我们通过训练场景草图语义分割的新计算模型，展示新数据集如何实现多种应用，包括图像检索，草图着色，编辑和字幕等，展示了SketchyScene的潜在影响。数据集和代码可以在https找到：//github.com/SketchyScene/SketchyScene。
URL
https://arxiv.org/abs/1808.02473
