6 papers
TTSD-FAR: Test-Time Self-Distillation with Fisher-Anchored Restoration for Missing-Modality Emotion Recognition in LVLMs
Muhammad Haseeb Aslam, Alessandro Koerich, Marco Pedersoli +2
Large video-language models (LVLMs) have shown remarkable performance on multimodal tasks like multimodal emotion recognition (ER) in the wild. ER is inherently multimodal, requiri…
From Affect to Complex Behavior: Advancing Multimodal Human-Centered AI at the 10th ABAW Workshop & Competition
Dimitrios Kollias, Panagiotis Tzirakis, Alan Cowen +10
The 10th Affective & Behavior Analysis in-the-Wild (ABAW) Workshop and Competition, held at CVPR 2026, continues to advance research on modelling, analysis, understanding of human…
Multimodal Ambivalence/Hesitancy Recognition in Videos for Personalized Digital Health Interventions
Manuela González-González, Soufiane Belharbi, Muhammad Osama Zeeshan +8
Using behavioural science, health interventions focus on behaviour change by providing a framework to help patients acquire and maintain healthy habits that improve medical outcome…
BAH Dataset for Ambivalence/Hesitancy Recognition in Videos for Digital Behavioural Change
Manuela González-González, Soufiane Belharbi, Muhammad Osama Zeeshan +6
Ambivalence and hesitancy (A/H), closely related constructs, are the primary reasons why individuals delay, avoid, or abandon health behaviour changes. They are subtle and conflict…
Learning from Stochastic Teacher Representations Using Student-Guided Knowledge Distillation
Muhammad Haseeb Aslam, Clara Martinez, Marco Pedersoli +3
Advances in self-distillation have shown that when knowledge is distilled from a teacher to a student using the same deep learning (DL) architecture, the student performance can su…
Multi Teacher Privileged Knowledge Distillation for Multimodal Expression Recognition
Muhammad Haseeb Aslam, Marco Pedersoli, Alessandro Lameiras Koerich +1
Human emotion is a complex phenomenon conveyed and perceived through facial expressions, vocal tones, body language, and physiological signals. Multimodal emotion recognition syste…