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 …

This paper introduces a convolutional neural network (CNN) semantic re-ranking system to
enhance the performance of sketch-based image retrieval (SBIR). Distinguished from the …

We propose a deep hashing framework for sketch retrieval that, for the first time, works on a
multi-million scale human sketch dataset. Leveraging on this large dataset, we explore a few …

Due to the succinct nature of free-hand sketch drawings, sketch-based image retrieval
(SBIR) has abundant practical use cases in consumer electronics. However, SBIR remains a …

Due to lack of data, overfitting ubiquitously exists in real-world applications of deep neural
networks (DNNs). We propose advanced dropout, a model-free methodology, to mitigate …

Sketch has been employed as an effective communication tool to express the abstract and
intuitive meaning of object. While content-based sketch recognition has been studied for …

Sketch-based image retrieval (SBIR) is challenging due to the inherent domain-gap
between sketch and photo. Compared with pixel-perfect depictions of photos, sketches are …

With the popularity of electronic touch-screen and pressure sensing devices, fine-grained
sketch based image retrieval (FG-SBIR) has become a research hotspot. In this paper, we …

Fine-Grained Sketch-Based Image Retrieval (FG-SBIR) is to use free-hand sketches as
queries to perform instance-level retrieval in an image gallery. Existing works usually …

Abstract Fine-grained Sketch-based Image Retrieval (FG-SBIR), which utilizes hand-drawn
sketches to search the target object images, has recently drawn much attention. It is a …