Please use this identifier to cite or link to this item:
https://dspace.iiti.ac.in/handle/123456789/15096
Title: | Demystifying Visual Features of Movie Posters for Multilabel Genre Identification |
Authors: | Chattopadhyay, Soumi |
Keywords: | Movie genre identification;movie poster;multilabel classification;transformer network |
Issue Date: | 2024 |
Publisher: | Institute of Electrical and Electronics Engineers Inc. |
Citation: | Nareti, U. K., Adak, C., & Chattopadhyay, S. (2024). Demystifying Visual Features of Movie Posters for Multilabel Genre Identification. IEEE Transactions on Computational Social Systems. Scopus. https://doi.org/10.1109/TCSS.2024.3481157 |
Abstract: | In the film industry, movie posters have been an essential part of advertising and marketing for many decades and continue to play a vital role even today in the form of digital posters through online, social media, and over-the-top (OTT) platforms. Typically, movie posters can effectively promote and communicate the essence of a film, such as its genre, visual style/tone, vibe, and storyline cue/theme, which are essential to attract potential viewers. Identifying the genres of a movie often has significant practical applications in recommending the film to target audiences. Previous studies on genre identification have primarily focused on sources such as plot synopses, subtitles, metadata, movie scenes, and trailer videos however, posters precede the availability of these sources and provide prerelease implicit information to generate mass interest. In this article, we work for automated multilabel movie genre identification only from poster images, without any aid of additional textual/metadata/video information about movies, which is one of the earliest attempts of its kind. Here, we present a deep transformer network with a probabilistic module to identify the movie genres exclusively from the poster. For experiments, we procured 13,882 number of posters of 13 genres from the Internet movie database (IMDb), where our model performances were encouraging and even outperformed some major contemporary architectures. © 2014 IEEE. |
URI: | https://doi.org/10.1109/TCSS.2024.3481157 https://dspace.iiti.ac.in/handle/123456789/15096 |
ISSN: | 2329-924X |
Type of Material: | Journal Article |
Appears in Collections: | Department of Computer Science and Engineering |
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.
Altmetric Badge: