Comic Characters Detection Using Deep Learning

Comic characters detection has been an interesting area in comic analysis as it not only allows more efficient indexation and retrieval for comic books but also yields an adequate understanding of comics so as to help better creating the digital form of comic books. In recent years, several methods that have been proposed to extract/detect characters from comics, have given reasonable performance. However, they always use their datasets to evaluate the methods without comparing with other works or experimenting on a standard dataset. In this work, we take advantage of the recent and significant development of deep learning to apply it to comic character detection. We use the latest object detection deep networks to train the comic characters detector based on our proposed dataset. By experimenting on our proposed dataset and also on available datasets from previous works, we have found that this method significantly outperforms existing methods. We believe that this state-of-the-art approach can be considered as a reliable baseline method to compare and better understand future detection techniques.