Recent Submissions

  • Using player's body-orientation to model pass feasibility in soccer 

    Arbués-Sangüesa, Adrià; Fernández de la Rosa, Javier Eduardo; Ballester, Coloma; Haro, Gloria; Martín, Adrián (2020)
    Conference report
    Open Access
    Given a monocular video of a soccer match, this paper presents a computational model to estimate the most feasible pass at any given time. The method leverages offensive player's orientation (plus their location) and ...
  • The TALP-UPC participation in WMT21 news translation task: an mBART-based NMT approach 

    Escolano Peinado, Carlos; Tsiamas, Ioannis; Basta, Christine Raouf Saad; Ferrando Monsonís, Javier; Ruiz Costa-Jussà, Marta; Rodríguez Fonollosa, José Adrián (Association for Computational Linguistics, 2021)
    Conference report
    Open Access
    This paper describes the submission to the WMT 2021 news translation shared task by the UPC Machine Translation group. The goal of the task is to translate German to French (De-Fr) and French to German (Fr-De). Our submission ...
  • Neural cellular automata manifold 

    Hernández Ruiz, Alejandro José; Vilalta Arias, Armand; Moreno-Noguer, Francesc (IEEE Computer Society Conference Publishing Services (CPS), 2021)
    Conference report
    Open Access
    Very recently, the Neural Cellular Automata (NCA) has been proposed to simulate the morphogenesis process with deep networks. NCA learns to grow an image starting from a fixed single pixel. In this work, we show that the ...
  • Choosing the root of the tree decomposition when solving WCSPs: preliminary results 

    Petrova, Aleksandra; Larrosa Bondia, Francisco Javier; Rollón Rico, Emma (IOS Press, 2021)
    Conference report
    Open Access
    In this paper we analyze the effect of selecting the root in a tree decomposition when using decomposition-based backtracking algorithms. We focus on optimization tasks for Graphical Models using the BTD algorithm. We show ...
  • Applying and verifying an explainability method based on policy graphs in the context of reinforcement learning 

    Climent Muñoz, Antoni; Gnatyshak, Dmitry; Álvarez Napagao, Sergio (IOS Press, 2021)
    Conference report
    Open Access
    The advancement on explainability techniques is quite relevant in the field of Reinforcement Learning (RL) and its applications can be beneficial for the development of intelligent agents that are understandable by humans ...
  • Everything transformers: Recognition, classification and normalisation of professions and family relations 

    Medina Herrera, Salvador; Turmo Borras, Jorge (CEUR-WS.org, 2021)
    Conference report
    Open Access
    This document describes the system submitted by TALP team for IberLEF 2021’s MEDDOPROF Shared Task. The joint occupation mention identification and family relation classification model is composed of a pre-trained DistilBERT ...
  • Real-time multimodal emotion classification system in E-Learning context 

    Arijit, Nandi; Xhafa Xhafa, Fatos; Subirats Maté, Laia; Fort, Santiago (Springer, 2021)
    Conference report
    Restricted access - publisher's policy
    Emotions of learners are crucial and important in e-learning as they promote learning. To investigate the effects of emotions on improving and optimizing the outcomes of e-learning, machine learning models have been proposed ...
  • TALP at eHealth-KD Challenge 2020: Multi-level recurrent and convolutional neural networks for joint classification of key-phrases and relations 

    Medina Herrera, Salvador; Turmo Borras, Jorge (CEUR-WS.org, 2020)
    Conference report
    Open Access
    This article describes the model presented by the TALP Team to IberLEF’s eHealth Knowledge Discovery 2020 shared task[1]. The model iterates over the idea of using a single model for simultaneously identify key-phrases and ...
  • Denoising wavefront sensor image with deep neural networks 

    Pou Mulet, Bartomeu; Quiñones Moreno, Eduardo; Gratadour, Damien; Martín Muñoz, Mario (International Society for Photo-Optical Instrumentation Engineers (SPIE), 2020)
    Conference report
    Open Access
    A classical closed-loop adaptive optics system with a Shack-Hartmann wavefront sensor (WFS) relies on a center of gravity approach to process the WFS information and an integrator with gain to produce the commands to a ...
  • Textual visual semantic dataset for text spotting 

    Sabir, Ahmed; Moreno-Noguer, Francesc; Padró, Lluís (Institute of Electrical and Electronics Engineers (IEEE), 2020)
    Conference report
    Open Access
    Text Spotting in the wild consists of detecting and recognizing text appearing in images (e.g. signboards, traffic signals or brands in clothing or objects). This is a challenging problem due to the complexity of the context ...
  • Building graph representations of deep vector embeddings 

    Garcia Gasulla, Dario; Vilalta Arias, Armand; Parés Pont, Ferran; Moreno Vázquez, Jonatan; Ayguadé Parra, Eduard; Labarta Mancho, Jesús José; Cortés García, Claudio Ulises; Suzumura, Toyotaro (Association for Computational Linguistics, 2017)
    Conference lecture
    Open Access
    Patterns stored within pre-trained deep neural networks compose large and powerful descriptive languages that can be used for many different purposes. Typically, deep network representations are implemented within vector ...
  • Full-network embedding in a multimodal embedding pipeline 

    Vilalta Arias, Armand; Garcia Gasulla, Dario; Parés Pont, Ferran; Moreno Vázquez, Jonatan; Ayguadé Parra, Eduard; Labarta Mancho, Jesús José; Cortés García, Claudio Ulises; Suzumura, Toyotaro (Association for Computational Linguistics, 2017)
    Conference lecture
    Open Access
    The current state-of-the-art for image annotation and image retrieval tasks is obtained through deep neural networks, which combine an image representation and a text representation into a shared embedding space. In this ...

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