388 citations · 971 across the 17 of their papers we have counts for
21 papers
7th ABAW Competition: Multi-Task Learning and Compound Expression Recognition
Dimitrios Kollias, Stefanos Zafeiriou, Irene Kotsia +4
This paper describes the 7th Affective Behavior Analysis in-the-wild (ABAW) Competition, which is part of the respective Workshop held in conjunction with ECCV 2024. The 7th ABAW C…
The 6th Affective Behavior Analysis in-the-wild (ABAW) Competition
Dimitrios Kollias, Panagiotis Tzirakis, Alan Cowen +6
This paper describes the 6th Affective Behavior Analysis in-the-wild (ABAW) Competition, which is part of the respective Workshop held in conjunction with IEEE CVPR 2024. The 6th A…
Distribution Matching for Multi-Task Learning of Classification Tasks: a Large-Scale Study on Faces & Beyond
Dimitrios Kollias, Viktoriia Sharmanska, Stefanos Zafeiriou
Multi-Task Learning (MTL) is a framework, where multiple related tasks are learned jointly and benefit from a shared representation space, or parameter transfer. To provide suffici…
ABAW: Valence-Arousal Estimation, Expression Recognition, Action Unit Detection & Emotional Reaction Intensity Estimation Challenges
Dimitrios Kollias, Panagiotis Tzirakis, Alice Baird +2
The fifth Affective Behavior Analysis in-the-wild (ABAW) Competition is part of the respective ABAW Workshop which will be held in conjunction with IEEE Computer Vision and Pattern…
ABAW: Learning from Synthetic Data & Multi-Task Learning Challenges
Dimitrios Kollias
This paper describes the fourth Affective Behavior Analysis in-the-wild (ABAW) Competition, held in conjunction with European Conference on Computer Vision (ECCV), 2022. The 4th AB…
MixAugment & Mixup: Augmentation Methods for Facial Expression Recognition
Andreas Psaroudakis, Dimitrios Kollias
Automatic Facial Expression Recognition (FER) has attracted increasing attention in the last 20 years since facial expressions play a central role in human communication. Most FER…
ABAW: Valence-Arousal Estimation, Expression Recognition, Action Unit Detection & Multi-Task Learning Challenges
Dimitrios Kollias
This paper describes the third Affective Behavior Analysis in-the-wild (ABAW) Competition, held in conjunction with IEEE International Conference on Computer Vision and Pattern Rec…
Analysing Affective Behavior in the second ABAW2 Competition
Dimitrios Kollias, Irene Kotsia, Elnar Hajiyev +1
The Affective Behavior Analysis in-the-wild (ABAW2) 2021 Competition is the second -- following the first very successful ABAW Competition held in conjunction with IEEE FG 2020- Co…
Distribution Matching for Heterogeneous Multi-Task Learning: a Large-scale Face Study
Dimitrios Kollias, Viktoriia Sharmanska, Stefanos Zafeiriou
Multi-Task Learning has emerged as a methodology in which multiple tasks are jointly learned by a shared learning algorithm, such as a DNN. MTL is based on the assumption that the…
Affect Analysis in-the-wild: Valence-Arousal, Expressions, Action Units and a Unified Framework
Dimitrios Kollias, Stefanos Zafeiriou
Affect recognition based on subjects' facial expressions has been a topic of major research in the attempt to generate machines that can understand the way subjects feel, act and r…
Analysing Affective Behavior in the First ABAW 2020 Competition
Dimitrios Kollias, Attila Schulc, Elnar Hajiyev +1
The Affective Behavior Analysis in-the-wild (ABAW) 2020 Competition is the first Competition aiming at automatic analysis of the three main behavior tasks of valence-arousal estima…
Face Behavior a la carte: Expressions, Affect and Action Units in a Single Network
Dimitrios Kollias, Viktoriia Sharmanska, Stefanos Zafeiriou
Automatic facial behavior analysis has a long history of studies in the intersection of computer vision, physiology and psychology. However it is only recently, with the collection…
Exploiting multi-CNN features in CNN-RNN based Dimensional Emotion Recognition on the OMG in-the-wild Dataset
Dimitrios Kollias, Stefanos Zafeiriou
This paper presents a novel CNN-RNN based approach, which exploits multiple CNN features for dimensional emotion recognition in-the-wild, utilizing the One-Minute Gradual-Emotion (…
Expression, Affect, Action Unit Recognition: Aff-Wild2, Multi-Task Learning and ArcFace
Dimitrios Kollias, Stefanos Zafeiriou
Affective computing has been largely limited in terms of available data resources. The need to collect and annotate diverse in-the-wild datasets has become apparent with the rise o…
Photorealistic Facial Synthesis in the Dimensional Affect Space
Dimitrios Kollias, Shiyang Cheng, Maja Pantic +1
This paper presents a novel approach for synthesizing facial affect, which is based on our annotating 600,000 frames of the 4DFAB database in terms of valence and arousal. The inpu…
A Multi-Task Learning & Generation Framework: Valence-Arousal, Action Units & Primary Expressions
Dimitrios Kollias, Stefanos Zafeiriou
Over the past few years many research efforts have been devoted to the field of affect analysis. Various approaches have been proposed for: i) discrete emotion recognition in terms…
Aff-Wild2: Extending the Aff-Wild Database for Affect Recognition
Dimitrios Kollias, Stefanos Zafeiriou
Automatic understanding of human affect using visual signals is a problem that has attracted significant interest over the past 20 years. However, human emotional states are quite…
Deep Neural Network Augmentation: Generating Faces for Affect Analysis
Dimitrios Kollias, Shiyang Cheng, Evangelos Ververas +2
This paper presents a novel approach for synthesizing facial affect; either in terms of the six basic expressions (i.e., anger, disgust, fear, joy, sadness and surprise), or in ter…
Training Deep Neural Networks with Different Datasets In-the-wild: The Emotion Recognition Paradigm
Dimitrios Kollias, Stefanos Zafeiriou
A novel procedure is presented in this paper, for training a deep convolutional and recurrent neural network, taking into account both the available training data set and some info…
A Multi-component CNN-RNN Approach for Dimensional Emotion Recognition in-the-wild
Dimitrios Kollias, Stefanos Zafeiriou
This paper presents our approach to the One-Minute Gradual-Emotion Recognition (OMG-Emotion) Challenge, focusing on dimensional emotion recognition through visual analysis of the p…
Deep Affect Prediction in-the-wild: Aff-Wild Database and Challenge, Deep Architectures, and Beyond
Dimitrios Kollias, Panagiotis Tzirakis, Mihalis A. Nicolaou +5
Automatic understanding of human affect using visual signals is of great importance in everyday human-machine interactions. Appraising human emotional states, behaviors and reactio…