24 citations · 57 across the 7 of their papers we have counts for
7 papers
Machine Learning-based Lie Detector applied to a Novel Annotated Game Dataset
Nuria Rodriguez-Diaz, Decky Aspandi, Federico Sukno +1
Lie detection is considered a concern for everyone in their day to day life given its impact on human interactions. Thus, people normally pay attention to both what their interlocu…
An Enhanced Adversarial Network with Combined Latent Features for Spatio-Temporal Facial Affect Estimation in the Wild
Decky Aspandi, Federico Sukno, Björn Schuller +1
Affective Computing has recently attracted the attention of the research community, due to its numerous applications in diverse areas. In this context, the emergence of video-based…
Adversarial-based neural networks for affect estimations in the wild
Decky Aspandi, Adria Mallol-Ragolta, Björn Schuller +1
There is a growing interest in affective computing research nowadays given its crucial role in bridging humans with computers. This progress has been recently accelerated due to th…
End-to-end facial and physiological model for Affective Computing and applications
Joaquim Comas, Decky Aspandi, Xavier Binefa
In recent years, Affective Computing and its applications have become a fast-growing research topic. Furthermore, the rise of Deep Learning has introduced significant improvements…
Learning Disentangled Representations with Reference-Based Variational Autoencoders
Adria Ruiz, Oriol Martinez, Xavier Binefa +1
Learning disentangled representations from visual data, where different high-level generative factors are independently encoded, is of importance for many computer vision tasks. So…
Multi-Instance Dynamic Ordinal Random Fields for Weakly-supervised Facial Behavior Analysis
Adria Ruiz, Ognjen Rudovic, Xavier Binefa +1
We propose a Multi-Instance-Learning (MIL) approach for weakly-supervised learning problems, where a training set is formed by bags (sets of feature vectors or instances) and only…