Learning about Fashion exploiting the Big Multimedia Data

We here propose to collect and analyze large amounts of multimedia data from different public and private sources, in the form of text, image, video, to predict relevant information about specific quantities related to fashion brands, such as their sales volumes and/or trends. To this aim, we deem deep learning techniques as the suitable instrument capable of managing extremely large amounts of multimedia data. While a few works exist in literature on learning applications in the fashion area, where text is used to perform sentiment analysis operations, limited research has also considered images and videos in this context. In this paper, starting with an overview of the state of the art of the applications of artificial intelligence for fashion, we set the stage for a holistic approach for the deep learning based analysis of multimedia data related to fashion.