Knowledge Amalgamation for Single-Shot Context-Aware Emotion Recognition

Tristan Cladière, Olivier Alata, Christophe Ducottet, Hubert Konik, Anne-Claire Legrand

2025

Abstract

Fine-grained emotion recognition using the whole context inside images is a challenging task. Usually, the approaches to solve this problem analyze the scene from different aspects, for example people, place, object or interactions, and make a final prediction that takes all this information into account. Despite giving promising results, this requires specialized pre-trained models, and multiple pre-processing steps, which inevitably results in long and complex frameworks. To obtain a more practicable solution that would work in real time scenario with limited resources, we propose a method inspired by the amalgamation process to incorporate specialized knowledge from multiple teachers inside a student composed of a single architecture. Moreover, the student is not only capable of treating all subjects simultaneously by creating emotion maps, but also to detect the subjects in a bottom-up manner. We also compare our approach with the traditional method of fine-tuning pre-trained models, and show its superiority on two databases used in the context-aware emotion recognition field.

Paper Citation

in Harvard Style

Cladière T., Alata O., Ducottet C., Konik H. and Legrand A. (2025). Knowledge Amalgamation for Single-Shot Context-Aware Emotion Recognition. In Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 2: VISAPP; ISBN 978-989-758-728-3, SciTePress, pages 410-419. DOI: 10.5220/0013169800003912

in Bibtex Style

@conference{visapp25,
author={Tristan Cladière and Olivier Alata and Christophe Ducottet and Hubert Konik and Anne-Claire Legrand},
title={Knowledge Amalgamation for Single-Shot Context-Aware Emotion Recognition},
booktitle={Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 2: VISAPP},
year={2025},
pages={410-419},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013169800003912},
isbn={978-989-758-728-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 2: VISAPP
TI - Knowledge Amalgamation for Single-Shot Context-Aware Emotion Recognition
SN - 978-989-758-728-3
AU - Cladière T.
AU - Alata O.
AU - Ducottet C.
AU - Konik H.
AU - Legrand A.
PY - 2025
SP - 410
EP - 419
DO - 10.5220/0013169800003912
PB - SciTePress