755 citations · 2.7k across the 91 of their papers we have counts for
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Facial Emotion Recognition using Deep Residual Networks in Real-World Environments
Panagiotis Tzirakis, Dénes Boros, Elnar Hajiyev +1
Automatic affect recognition using visual cues is an important task towards a complete interaction between humans and machines. Applications can be found in tutoring systems and hu…
A Physiologically-Adapted Gold Standard for Arousal during Stress
Alice Baird, Lukas Stappen, Lukas Christ +3
Emotion is an inherently subjective psychophysiological human-state and to produce an agreed-upon representation (gold standard) for continuous emotion requires a time-consuming an…
MeDaS: An open-source platform as service to help break the walls between medicine and informatics
Liang Zhang, Johann Li, Ping Li +7
In the past decade, deep learning (DL) has achieved unprecedented success in numerous fields including computer vision, natural language processing, and healthcare. In particular,…
Domain Adaptation with Joint Learning for Generic, Optical Car Part Recognition and Detection Systems (Go-CaRD)
Lukas Stappen, Xinchen Du, Vincent Karas +2
Systems for the automatic recognition and detection of automotive parts are crucial in several emerging research areas in the development of intelligent vehicles. They enable, for…
Synthesising 3D Facial Motion from "In-the-Wild" Speech
Panagiotis Tzirakis, Athanasios Papaioannou, Alexander Lattas +3
Synthesising 3D facial motion from speech is a crucial problem manifesting in a multitude of applications such as computer games and movies. Recently proposed methods tackle this p…
audEERING's approach to the One-Minute-Gradual Emotion Challenge
Andreas Triantafyllopoulos, Hesam Sagha, Florian Eyben +1
This paper describes audEERING's submissions as well as additional evaluations for the One-Minute-Gradual (OMG) emotion recognition challenge. We provide the results for audio and…
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…
End2You -- The Imperial Toolkit for Multimodal Profiling by End-to-End Learning
Panagiotis Tzirakis, Stefanos Zafeiriou, Bjorn W. Schuller
We introduce End2You -- the Imperial College London toolkit for multimodal profiling by end-to-end deep learning. End2You is an open-source toolkit implemented in Python and is bas…
End-to-End Multimodal Emotion Recognition using Deep Neural Networks
Panagiotis Tzirakis, George Trigeorgis, Mihalis A. Nicolaou +2
Automatic affect recognition is a challenging task due to the various modalities emotions can be expressed with. Applications can be found in many domains including multimedia retr…
Deep Structured Learning for Facial Action Unit Intensity Estimation
Robert Walecki, Ognjen, Rudovic +3
We consider the task of automated estimation of facial expression intensity. This involves estimation of multiple output variables (facial action units --- AUs) that are structural…
DeepCoder: Semi-parametric Variational Autoencoders for Automatic Facial Action Coding
Dieu Linh Tran, Robert Walecki, Ognjen Rudovic +3
Human face exhibits an inherent hierarchy in its representations (i.e., holistic facial expressions can be encoded via a set of facial action units (AUs) and their intensity). Vari…
openXBOW - Introducing the Passau Open-Source Crossmodal Bag-of-Words Toolkit
Maximilian Schmitt, Björn W. Schuller
We introduce openXBOW, an open-source toolkit for the generation of bag-of-words (BoW) representations from multimodal input. In the BoW principle, word histograms were first used…
AVEC 2016 - Depression, Mood, and Emotion Recognition Workshop and Challenge
Michel Valstar, Jonathan Gratch, Bjorn Schuller +7
The Audio/Visual Emotion Challenge and Workshop (AVEC 2016) "Depression, Mood and Emotion" will be the sixth competition event aimed at comparison of multimedia processing and mach…
A deep matrix factorization method for learning attribute representations
George Trigeorgis, Konstantinos Bousmalis, Stefanos Zafeiriou +1
Semi-Non-negative Matrix Factorization is a technique that learns a low-dimensional representation of a dataset that lends itself to a clustering interpretation. It is possible tha…
6th International Symposium on Attention in Cognitive Systems 2013
Lucas Paletta, Laurent Itti, Björn Schuller +1
This volume contains the papers accepted at the 6th International Symposium on Attention in Cognitive Systems (ISACS 2013), held in Beijing, August 5, 2013. The aim of this symposi…