Story Generation from Visual Inputs: Techniques, Related Tasks, and Challenges

Creating engaging narratives from visual data is crucial for automated digital media consumption, assistive technologies, and interactive entertainment. This survey covers methodologies used in the generation of these narratives, focusing on their principles, strengths, and limitations. The survey also covers tasks related to automatic story generation, such as image and video captioning, and Visual Question Answering. These tasks share common challenges with Visual Story Generation (VSG) and have served as inspiration for the techniques used in the field. We analyze the main datasets and evaluation metrics, providing a critical perspective on their limitations.

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Information
Published
2025-09-18
DOI
https://doi.org/10.3390/info16090812
Citations
1
Primary Topic
Multimodal Machine Learning Applications
Type
article
Field-Weighted Citation Impact
1.28
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article

Story Generation from Visual Inputs: Techniques, Related Tasks, and Challenges

David Martins de Matos, Eugénio Ribeiro, Daniel A. P. Oliveira
1 citations
Information
Multimodal Machine Learning Applications
1.28
article

Story Generation from Visual Inputs: Techniques, Related Tasks, and Challenges

David Martins de Matos, Eugénio Ribeiro, Daniel A. P. Oliveira
article en
1 citations

Abstract

Creating engaging narratives from visual data is crucial for automated digital media consumption, assistive technologies, and interactive entertainment. This survey covers methodologies used in the generation of these narratives, focusing on their principles, strengths, and limitations. The survey also covers tasks related to automatic story generation, such as image and video captioning, and Visual Question Answering. These tasks share common challenges with Visual Story Generation (VSG) and have served as inspiration for the techniques used in the field. We analyze the main datasets and evaluation metrics, providing a critical perspective on their limitations.

InformationVol. 16(9)
Iscte – Instituto Universitário de Lisboa (PT), Instituto de Engenharia de Sistemas e Computadores Investigação e Desenvolvimento (PT), University of Lisbon (PT), Universidade Politécnica de Lisboa (PT)
Openalex Percentile: Top 16%
Multimodal Machine Learning Applications
1.28
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