20 citations · 22 across the 25 of their papers we have counts for
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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…
Test-Time Adaptation with Online Personalized Energy-Based Cache for Fine-Grained Video Expression Recognition
Masoumeh Sharafi, Muhammad Osama Zeeshan, Soufiane Belharbi +3
Facial expression recognition (FER) in videos is challenging because models must identify subtle, temporally evolving affective states that vary across individuals. Although vision…
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…
CLIP-AUTT: Test-Time Personalization with Action Unit Prompting for Fine-Grained Video Emotion Recognition
Muhammad Osama Zeeshan, Masoumeh Sharafi, Benoit Savary +3
Personalization in emotion recognition (ER) is essential for accurate interpretation of subtle and subject-specific expressive patterns. Recent advances in vision-language models (…
Test-Time Adaptation via Cache Personalization for Facial Expression Recognition in Videos
Masoumeh Sharafi, Muhammad Osama Zeeshan, Soufiane Belharbi +3
Facial expression recognition (FER) in videos requires model personalization to capture considerable variation across subjects. Vision-language models (VLMs) offer strong transfer…
Brazilian Portuguese Image Captioning with Transformers: A Study on Cross-Native-Translated Dataset
Gabriel Bromonschenkel, Alessandro L. Koerich, Thiago M. Paixão +1
Image captioning (IC) refers to the automatic generation of natural language descriptions for images, with applications ranging from social media content generation to assisting in…
MuSACo: Multimodal Subject-Specific Selection and Adaptation for Expression Recognition with Co-Training
Muhammad Osama Zeeshan, Natacha Gillet, Alessandro Lameiras Koerich +3
Personalized expression recognition (ER) involves adapting a machine learning model to subject-specific data for improved recognition of expressions with considerable interpersonal…
Personalized Feature Translation for Expression Recognition: An Efficient Source-Free Domain Adaptation Method
Masoumeh Sharafi, Soufiane Belharbi, Muhammad Osama Zeeshan +6
Facial expression recognition (FER) models are widely used in video-based affective computing applications, such as human-computer interaction and healthcare monitoring. However, d…
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…
Progressive Multi-Source Domain Adaptation for Personalized Facial Expression Recognition
Muhammad Osama Zeeshan, Marco Pedersoli, Alessandro Lameiras Koerich +1
Personalized facial expression recognition (FER) involves adapting a machine learning model using samples from labeled sources and unlabeled target domains. Given the challenges of…
Disentangled Source-Free Personalization for Facial Expression Recognition with Neutral Target Data
Masoumeh Sharafi, Emma Ollivier, Muhammad Osama Zeeshan +5
Facial Expression Recognition (FER) from videos is a crucial task in various application areas, such as human-computer interaction and health diagnosis and monitoring (e.g., assess…
AI-Driven Early Mental Health Screening: Analyzing Selfies of Pregnant Women
Gustavo A. Basílio, Thiago B. Pereira, Alessandro L. Koerich +9
Major Depressive Disorder and anxiety disorders affect millions globally, contributing significantly to the burden of mental health issues. Early screening is crucial for effective…
Spatial Action Unit Cues for Interpretable Deep Facial Expression Recognition
Soufiane Belharbi, Marco Pedersoli, Alessandro Lameiras Koerich +2
Although state-of-the-art classifiers for facial expression recognition (FER) can achieve a high level of accuracy, they lack interpretability, an important feature for end-users.…
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…
Textualized and Feature-based Models for Compound Multimodal Emotion Recognition in the Wild
Nicolas Richet, Soufiane Belharbi, Haseeb Aslam +8
Systems for multimodal emotion recognition (ER) are commonly trained to extract features from different modalities (e.g., visual, audio, and textual) that are combined to predict i…
Joint Multimodal Transformer for Emotion Recognition in the Wild
Paul Waligora, Haseeb Aslam, Osama Zeeshan +5
Multimodal emotion recognition (MMER) systems typically outperform unimodal systems by leveraging the inter- and intra-modal relationships between, e.g., visual, textual, physiolog…
Alleviating Catastrophic Forgetting in Facial Expression Recognition with Emotion-Centered Models
Israel A. Laurensi, Alceu de Souza Britto, Jean Paul Barddal +1
Facial expression recognition is a pivotal component in machine learning, facilitating various applications. However, convolutional neural networks (CNNs) are often plagued by cata…
Guided Interpretable Facial Expression Recognition via Spatial Action Unit Cues
Soufiane Belharbi, Marco Pedersoli, Alessandro Lameiras Koerich +2
Although state-of-the-art classifiers for facial expression recognition (FER) can achieve a high level of accuracy, they lack interpretability, an important feature for end-users.…
Distilling Privileged Multimodal Information for Expression Recognition using Optimal Transport
Muhammad Haseeb Aslam, Muhammad Osama Zeeshan, Soufiane Belharbi +4
Deep learning models for multimodal expression recognition have reached remarkable performance in controlled laboratory environments because of their ability to learn complementary…
Subject-Based Domain Adaptation for Facial Expression Recognition
Muhammad Osama Zeeshan, Muhammad Haseeb Aslam, Soufiane Belharbi +4
Adapting a deep learning model to a specific target individual is a challenging facial expression recognition (FER) task that may be achieved using unsupervised domain adaptation (…