Publications

Few Labels are Enough! Semi-Supervised Graph Learning for Social Interaction

Published in Companion Publication of the 2021 International Conference on Multimodal Interaction, 2023

Recommended citation: Nicola Corbellini, Jhony H. Giraldo, Giovanna Varni, Gualtiero Volpe; Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops, 2023, pp. 3060-3068 https://openaccess.thecvf.com/content/ICCV2023W/ASI/html/Corbellini_Few_Labels_are_Enough_Semi-Supervised_Graph_Learning_for_Social_Interaction_ICCVW_2023_paper.html

An Exploratory Study on Group Potency Classification from Non-verbal Social Behaviours

Published in 12th International Workshop on Human Behavior Understanding, 2022

This a study about small teams social interaction binary classification with state-of-the-art machine learning algorithms and exploiting non-verbal socio-behavioural features.

Recommended citation: Corbellini, N., Ceccaldi, E., Varni, G., & Volpe, G. (2022, August). An Exploratory Study on Group Potency Classification from Non-verbal Social Behaviours. In 12th International Workshop on Human Behavior Understanding. Not available yet

Towards Human-Machine Collaboration: Multimodal Group Potency Estimation

Published in In INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION (ICMI 2022), 2022

Doctoral Consortium paper published in the context of the International Conference on Multimodal Interaction (ICMI22) illustrating the goals and stages of my PhD project.

Recommended citation: Nicola Corbellini. 2022. Towards Human-Machine Collaboration: Multimodal Group Potency Estimation. In INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION (ICMI 22), November 7–11, 2022, Bengaluru, India. ACM, New York, NY, USA https://doi.org/10.1145/3536221.3557035

Making Automatic Movement Features Extraction Suitable for Non-engineer Students

Published in Companion Publication of the 2021 International Conference on Multimodal Interaction, 2021

This paper is a software tool for automatic annotation of movement data.

Recommended citation: Corbellini, N. and Volpe, G., 2021, October. Making Automatic Movement Features Extraction Suitable for Non-engineer Students. In Companion Publication of the 2021 International Conference on Multimodal Interaction (pp. 153-157). https://dl.acm.org/doi/abs/10.1145/3461615.3485398