The new era of technology has brought us to the point where it is convenient for people to share their opinions over an abundance of platforms. These platforms have a provision for the users to express themselves in multiple forms of representations, including text, images, videos, and audio. This, however, makes it difficult for users to obtain all the key information about a topic, making the task of automatic multi-modal summarization (MMS) essential. In this paper, we present a comprehensive survey of the existing research in the area of MMS, covering various modalities like text, image, audio, and video. Apart from highlighting the different evaluation metrics and datasets used for the MMS task, our work also discusses the current challenges and future directions in this field.
@article{arxiv.2109.05199,
title = {A Survey on Multi-modal Summarization},
author = {Anubhav Jangra and Sourajit Mukherjee and Adam Jatowt and Sriparna Saha and Mohammad Hasanuzzaman},
journal= {arXiv preprint arXiv:2109.05199},
year = {2023}
}