Human sketch has already proved its worth in various visual understanding tasks (e.g., retrieval, segmentation, image-captioning, etc). In this paper, we reveal a new trait of sketches - that they are also salient. This is intuitive as sketching is a natural attentive process at its core. More specifically, we aim to study how sketches can be used as a weak label to detect salient objects present in an image. To this end, we propose a novel method that emphasises on how "salient object" could be explained by hand-drawn sketches. To accomplish this, we introduce a photo-to-sketch generation model that aims to generate sequential sketch coordinates corresponding to a given visual photo through a 2D attention mechanism. Attention maps accumulated across the time steps give rise to salient regions in the process. Extensive quantitative and qualitative experiments prove our hypothesis and delineate how our sketch-based saliency detection model gives a competitive performance compared to the state-of-the-art.

翻译：人类手绘已在多项视觉理解任务（如检索、分割、图像描述等）中证明了其价值。本文揭示了手绘的一个新特性——它们本身也具有显著性，这符合直觉，因为手绘本质上是一种自然的注意力聚焦过程。具体而言，我们旨在研究如何利用手绘作为弱标签来检测图像中的显著目标。为此，我们提出了一种新颖方法，重点阐述了“显著目标”如何通过手绘草图进行解释。为实现这一目标，我们引入了一个图像到草图生成模型，该模型通过二维注意力机制，生成与给定视觉图像对应的顺序草图坐标。注意力图随时间步累积的过程自然产生了显著性区域。大量定性和定量实验验证了我们的假设，并证明了基于手绘的显著性检测模型相比现有最先进方法具有竞争力的性能。