Work

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

Year: 2025

Type: article

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.

Source: Information

DOI: 10.3390/info16090812

Authors: Daniel A. P. Oliveira, Eugénio Ribeiro, David Martins de Matos

Institutions: Instituto de Engenharia de Sistemas e Computadores Investigação e Desenvolvimento, University of Lisbon, Institute for Systems Engineering and Computers, Instituto Superior Técnico, Iscte – Instituto Universitário de Lisboa

Language: English

Topic: Multimodal Machine Learning Applications

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $1,930

Funder: Fundação para a Ciência e a Tecnologia