Browsing by Author "Binefa i Valls, Xavier"

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  • Affective state-based framework for e-learning systems
    Rodríguez, Juan Antonio; Comas, Joaquim; Binefa i Valls, Xavier (IOS Press, 2021)
    Virtual learning and education have become crucial during the COVID19 pandemic, which has forced a rethink by teachers and educators into designing online content and the indirect interaction with students. In an face-to-face ...
  • Audio-visual gated-sequenced neural networks for affect recognition
    Aspandi, Decky; Sukno, Federico Mateo; Schuller, Björn; Binefa i Valls, Xavier (Institute of Electrical and Electronics Engineers (IEEE), 2022)
    The interest in automatic emotion recognition and the larger field of Affective Computing has recently gained momentum. The current emergence of large, video-based affect datasets offering rich multi-modal inputs facilitates ...
  • Composite recurrent network with internal denoising for facial alignment in still and video images in the wild
    Aspandi, Decky; Martinez, Oriol; Sukno, Federico Mateo; Binefa i Valls, Xavier (Elsevier, 2021)
    Facial alignment is an essential task for many higher level facial analysis applications, such as animation, human activity recognition and human - computer interaction. Although the recent availability of big datasets and ...
  • Covariance-based descriptors for pattern recognition in multiple feature spaces
    Cirujeda Santolaria, Pol (Universitat Pompeu Fabra, 2016-02-08)
    En aquesta tesi s’explora l’ús de descriptors basats en la covariància per tal de traslladar la observació de característiques dins de regions d’interès a un determinat espai descriptiu que utilitzi les matrius de covariància ...
  • Deep spatio-temporal neural network for facial analysis
    Aspandi Latif, Decky (Universitat Pompeu Fabra, 2021-03-24)
    Automatic Facial Analysis is one of the most important field of computer vision due to its significant impacts to the world we currently live in. Among many applications of Automatic Facial Analysis, Facial Alignment and ...
  • End-to-end facial and physiological model for affective computing and applications
    Comas, Joaquim; Aspandi, Decky; Binefa i Valls, Xavier (Institute of Electrical and Electronics Engineers (IEEE), 2020)
    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 in the emotion recognition system compared ...
  • An enhanced adversarial network with combined latent features for spatio-temporal facial affect estimation in the wild
    Aspandi, Decky; Sukno, Federico Mateo; Schuller, Björn; Binefa i Valls, Xavier (Scitepress, 2021)
    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 data allows to enrich the widely used ...
  • From emotions to action units with hidden and semi-hidden-task learning
    Ruiz, Adrià; Van de Weijer, Joost; Binefa i Valls, Xavier (Institute of Electrical and Electronics Engineers (IEEE), 2015)
    Limited annotated training data is a challenging problem in Action Unit recognition. In this paper, we investigate how the use of large databases labelled according to the 6 universal facial expressions can increase the ...
  • Fully end-to-end composite recurrent convolution network for deformable facial tracking in the wild
    Sukno, Federico Mateo; Aspandi, Decky; Martínez, Oriol; Sukno, Federico Mateo; Binefa i Valls, Xavier (Institute of Electrical and Electronics Engineers (IEEE), 2019)
    Human facial tracking is an important task in computer vision, which has recently lost pace compared to other facial analysis tasks. The majority of current available tracker possess two major limitations: their little use ...
  • Fusion of valence and arousal annotations through dynamic subjective ordinal modelling
    Ruiz, Adrià; Martinez, Oriol; Binefa i Valls, Xavier; Sukno, Federico Mateo (Institute of Electrical and Electronics Engineers (IEEE), 2017)
    An essential issue when training and validating computer vision systems for affect analysis is how to obtain reliable ground-truth labels from a pool of subjective annotations. In this paper, we address this problem when ...
  • Heatmap-guided balanced deep convolution networks for family classification in the wild
    Aspandi, Decky; Martínez, Oriol; Binefa i Valls, Xavier (Institute of Electrical and Electronics Engineers (IEEE), 2019)
    Automatic kinship recognition using Computer Vision, which aims to infer the blood relationship between individuals by only comparing their facial features, has started to gain attention recently. The introduction of large ...
  • Latent-based adversarial neural networks for facial affect estimations
    Aspandi, Decky; Mallol Ragolta, Adrià; Schuller, Björn; Binefa i Valls, Xavier (Institute of Electrical and Electronics Engineers (IEEE), 2020)
    There is a growing interest in affective computing research nowadays given its crucial role in bridging humans with computers. This progress has recently been accelerated due to the emergence of bigger dataset. One recent ...
  • Look-alike humans identified by facial recognition algorithms show genetic similarities
    Joshi, Ricky S.; Rigau, Maria; García-Prieto, Carlos A.; Castro de Moura, Manuel; Piñeyro, David; Moran, Sebastian; Davalos, Veronica; Carrión, Pablo; Ferrando-Bernal, Manuel, 1990-; Olalde Marquínez, Íñigo, 1987-; Lalueza Fox, Carles, 1965-; Navarro i Cuartiellas, Arcadi, 1969-; Fernández-Tena, Carles; Aspandi, Decky; Sukno, Federico Mateo; Binefa i Valls, Xavier; Valencia, Alfonso; Esteller, Manel (Elsevier, 2022)
    The human face is one of the most visible features of our unique identity as individuals. Interestingly, monozygotic twins share almost identical facial traits and the same DNA sequence but could exhibit differences in ...
  • Multi-instance dynamic ordinal random fields for weakly supervised dacial behavior analysis
    Ruiz, Adrià; Rudovic, Ognjen; Binefa i Valls, Xavier; Pantic, Maja (Institute of Electrical and Electronics Engineers (IEEE), 2018)
    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 labels at bag-level are provided. Specifically, ...
  • Multi-instance dynamic ordinal random fields for weakly-supervised pain intensity estimation
    Ruiz Ovejero, Adrià; Rudovic, Ognjen; Binefa i Valls, Xavier; Pantic, Maja (Springer, 2017)
    In this paper, we address the Multi-Instance-Learning (MIL) problem when bag labels are naturally represented as ordinal variables (Multi-Instance-Ordinal Regression). Moreover, we consider the case where bags are temporal ...
  • Robust facial alignment with internal denoising auto-encoder
    Aspandi, Decky; Martínez, Oriol; Sukno, Federico Mateo; Binefa i Valls, Xavier (Institute of Electrical and Electronics Engineers (IEEE), 2019)
    The development of facial alignment models is growing rapidly thanks to the availability of large facial landmarked datasets and powerful deep learning models. However, important challenges still remain for facial alignment ...
  • Template tracking of articulated objects using active contours
    Martinez Pujol, Oriol (Universitat Pompeu Fabra, 2016-04-19)
    En aquesta dissertació es fusionen dos dels temes tradicionals de la Visió per Computador: la segmentació i el seguiment d'objectes. Per a la segmentació s'utilitzen mètodes basats en "Active Contours (AC)" i per al seguiment ...
  • Weakly-supervised learning for automatic facial behaviour analysis
    Ruiz Ovejero, Adrià (Universitat Pompeu Fabra, 2017-12-05)
    In this Thesis we focus on Automatic Facial Behavior Analysis, which attempts to develop autonomous systems able to recognize and understand human facial expressions. Given the amount of information expressed by facial ...

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