3 citations · 5 across the 5 of their papers we have counts for
6 papers
A Sub-Layered Hierarchical Pyramidal Neural Architecture for Facial Expression Recognition
Henrique Siqueira, Pablo Barros, Sven Magg +2
In domains where computational resources and labeled data are limited, such as in robotics, deep networks with millions of weights might not be the optimal solution. In this paper,…
Disambiguating Affective Stimulus Associations for Robot Perception and Dialogue
Henrique Siqueira, Alexander Sutherland, Pablo Barros +3
Effectively recognising and applying emotions to interactions is a highly desirable trait for social robots. Implicitly understanding how subjects experience different kinds of act…
An Ensemble with Shared Representations Based on Convolutional Networks for Continually Learning Facial Expressions
Henrique Siqueira, Pablo Barros, Sven Magg +1
Social robots able to continually learn facial expressions could progressively improve their emotion recognition capability towards people interacting with them. Semi-supervised le…
Facial Expression Editing with Continuous Emotion Labels
Alexandra Lindt, Pablo Barros, Henrique Siqueira +1
Recently deep generative models have achieved impressive results in the field of automated facial expression editing. However, the approaches presented so far presume a discrete re…
Efficient Facial Feature Learning with Wide Ensemble-based Convolutional Neural Networks
Henrique Siqueira, Sven Magg, Stefan Wermter
Ensemble methods, traditionally built with independently trained de-correlated models, have proven to be efficient methods for reducing the remaining residual generalization error,…
The OMG-Emotion Behavior Dataset
Pablo Barros, Nikhil Churamani, Egor Lakomkin +3
This paper is the basis paper for the accepted IJCNN challenge One-Minute Gradual-Emotion Recognition (OMG-Emotion) by which we hope to foster long-emotion classification using neu…