Jack of many Faces: A Step Towards Facial Expression and Physiological State Analysis with a Single Network

Tariq, Abdullah and Mesak, Martin and Azad, R. Muhammad Atif and Gilani, Zulqarnain (2025) Jack of many Faces: A Step Towards Facial Expression and Physiological State Analysis with a Single Network. In: The 36th British Machine Vision Conference, 24th-27th Novemeber 2025, Sheffield, UK.

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Abstract

Facial feature analysis, particularly dynamic facial expression recognition, is essential in computer vision for understanding human emotions, behaviors, and physiological states. However, existing approaches often exhibit limited performance, stemming from inadequate modelling of facial dynamics, noise sensitivity, ambiguous expression semantics, and are generally specific to single-task scenarios. To address these issues, we propose a compact 3D spatio-temporal network capable of handling both expression recognition and physiological state analysis. Our network includes two custom modules: (1) Contrastive Adversarial Efficient Local Channel Attention (ConAdv-ELCA), which extracts and disentangles fine-grained local facial features, and (2) Efficient Global Channel Attention (EGCA), to capture local-global interactions. Unlike prior work, which predominantly evaluates models on similar datasets within single-task domains, our work has demonstrated the ability to generalize across different tasks that are based on facial analysis. Experimental results demonstrate that our model consistently achieves state-ofthe-art or near-state-of-the-art performance on blood alcohol concentration estimation, dynamic facial expression recognition, and driver fatigue detection.

Item Type:	Conference or Workshop Item (Paper)
Dates:	Date Event 1 August 2025 Accepted 27 November 2025 Published Online
Subjects:	CAH11 - computing > CAH11-01 - computing > CAH11-01-01 - computer science
Divisions:	Architecture, Built Environment, Computing and Engineering > Computer Science
Depositing User:	Gemma Tonks
Date Deposited:	24 Sep 2025 10:22
Last Modified:	24 Sep 2025 10:22
URI:	https://www.open-access.bcu.ac.uk/id/eprint/16654

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