A Survey on Multi-modal Summarization

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 article, we present a comprehensive survey of the existing research in the area of MMS, covering various modalities such as 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.

Automated summary

This article presents a comprehensive survey of existing research on automatic multi-modal summarization (MMS), covering various modalities such as text, image, audio, and video. It discusses the importance of MMS, highlights different evaluation metrics and datasets used for this task, and identifies current challenges and future directions in the field.