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Natural Language Generation from Visual Events: State-of-the-Art and Key Open Questions

Created by
  • Haebom

Author

Aditya K Surikuchi, Raquel Fernandez, Sandro Pezzelle

Outline

This paper considers the diverse tasks of generating natural language from image or video sequences as special cases of the more general problem of modeling the complex relationships between temporally unfolding visual events and the linguistic features used to interpret or describe them. While previous research has focused on various visual natural language processing tasks, the nature and extent of intermodal interactions have been lacking. Therefore, this paper presents five different tasks, examines the modeling and evaluation approaches used in these tasks, and identifies common challenges and future research directions.

Takeaways, Limitations

Takeaways: By emphasizing that modeling the relationship between visual events and language over time is central to various visual natural language generation tasks, we suggest research directions. We identify common problems and limitations of existing studies and raise important questions for future research.
Limitations: This paper does not present specific models or experimental results, but focuses primarily on analyzing existing research and suggesting future research directions. It may lack an in-depth analysis of the five challenges presented.
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