activity
20232026
most citedMMA-MRNNet: Harnessing Multiple Models of Affect and Dynamic Masked RNN for Precise Facial Expression Intensity Estimation

9 citations · 9 across the 10 of their papers we have counts for

collaborators

10 papers

cs.CV2026

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…

cs.CV2026

A Closed-Form Solution for Debiasing Vision-Language Models with Utility Guarantees Across Modalities and Tasks

Tangzheng Lian, Guanyu Hu, Yijing Ren +2

While Vision-Language Models (VLMs) have achieved remarkable performance across diverse downstream tasks, recent studies have shown that they can inherit social biases from the tra…

cs.LG2025

FairMT: Fairness for Heterogeneous Multi-Task Learning

Guanyu Hu, Tangzheng Lian, Na Yan +5

Fairness in machine learning has been extensively studied in single-task settings, while fair multi-task learning (MTL), especially with heterogeneous tasks (classification, detect…

cs.CV2025

CausalAffect: Causal Discovery for Facial Affective Understanding

Guanyu Hu, Tangzheng Lian, Dimitrios Kollias +2

Understanding human affect from facial behavior requires not only accurate recognition but also structured reasoning over the latent dependencies that drive muscle activations and…

cs.CV2025

Grounding Emotion Recognition with Visual Prototypes: VEGA -- Revisiting CLIP in MERC

Guanyu Hu, Dimitrios Kollias, Xinyu Yang

Multimodal Emotion Recognition in Conversations remains a challenging task due to the complex interplay of textual, acoustic and visual signals. While recent models have improved p…

cs.LG2025

Fair Domain Generalization: An Information-Theoretic View

Tangzheng Lian, Guanyu Hu, Dimitrios Kollias +2

Domain generalization (DG) and algorithmic fairness are two critical challenges in machine learning. However, most DG methods focus only on minimizing expected risk in the unseen t…

cs.CV2024

Behaviour4All: in-the-wild Facial Behaviour Analysis Toolkit

Dimitrios Kollias, Chunchang Shao, Odysseus Kaloidas +1

In this paper, we introduce Behavior4All, a comprehensive, open-source toolkit for in-the-wild facial behavior analysis, integrating Face Localization, Valence-Arousal Estimation,…

cs.CV2024

Rethinking Affect Analysis: A Protocol for Ensuring Fairness and Consistency

Guanyu Hu, Dimitrios Kollias, Eleni Papadopoulou +3

Evaluating affect analysis methods presents challenges due to inconsistencies in database partitioning and evaluation protocols, leading to unfair and biased results. Previous stud…

cs.CV2024

Robust Facial Reactions Generation: An Emotion-Aware Framework with Modality Compensation

Guanyu Hu, Jie Wei, Siyang Song +4

The objective of the Multiple Appropriate Facial Reaction Generation (MAFRG) task is to produce contextually appropriate and diverse listener facial behavioural responses based on…

cs.CV2023★ 9 cited

MMA-MRNNet: Harnessing Multiple Models of Affect and Dynamic Masked RNN for Precise Facial Expression Intensity Estimation

Dimitrios Kollias, Andreas Psaroudakis, Anastasios Arsenos +4

This paper presents MMA-MRNNet, a novel deep learning architecture for dynamic multi-output Facial Expression Intensity Estimation (FEIE) from video data. Traditional approaches to…