Conference Agenda
Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).
|
Daily Overview |
| Session | |
|
MCI-Demo Session Location: Foyer (Central lecture hall and seminar building) | |
| Presentation 7 | |
CUTIE: A human-in-the-loop interface for the generation of personalised and contextualised image captions 1: DFKI Deutsches Forschungszentrum für Künstliche Intelligenz, Deutschland; 2: Carl-von-Ossietzky Universität Oldenburg, Applied Artificial Intelligence, Deutschland Image captioning is an AI-complete task that bridges computer vision and natural language processing. Its goal is to generate textual descriptions for a given image. However, general-purpose image captioning often does not capture contextual information, such as information about the people present or the location the image was shot. To address this challenge, we propose a web-based tool that leverages automated image captioning, large foundation models, and additional deep learning modules such as object recognition and metadata analysis to accelerate the process of generating contextualised and personalised image captions. The tool allows users to create personalised and contextualised image captions efficiently. User interactions and feedback given to the various components are stored and later used for domain adaptation of the respective components. Our ultimate goal is to improve the efficiency and accuracy of creating personalised and contextualised image captions. | |
