A character network is a graph extracted from a narrative in which vertices represent
characters and edges correspond to interactions between them. A number of narrative …

Graph convolutional networks (GCNs) have a strong ability to learn graph representation
and have achieved good performance in a range of applications, including social …

With the rapid development of cartoon industry, various studies on two-dimensional (2D)
cartoon have been proposed for different application scenarios, such as quality assessment …

Drawn sequences of images are among our oldest records of human intelligence, appearing
on cave paintings, wall carvings, and ancient pottery, and they pervade across cultures from …

Comic character detection is becoming an exciting and growing research area in the domain
of machine learning. In this regard, recently, many methods are proposed to provide …

Face detection of comic characters is a necessary step in most applications, such as comic
character retrieval, automatic character classification and comic analysis. However, the …

In this paper, we introduce the cartoon faces in the wild (IIIT-CFW) database and associated
problems. This database contains 8,928 annotated images of cartoon faces of 100 public …

Among various elements of manga, character's face plays one of the most important role in
access and retrieval. We propose a DNN-based method to do manga face detection, which …

The way we understand a narrative sequence of images may seem effortless, given the
prevalence of comics and picture stories across contemporary society. Yet, visual narrative …

Cartoon face recognition is challenging as they typically have smooth color regions and
emphasized edges, the key to recognizing cartoon faces is to precisely perceive their sparse …