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] . Exploiting Structural Hierarchy in Articulated Objects Towards Robust Motion Capture. In V Conference on Articulated Motion and Deformable Objects (AMDO). 2008. pp. 82–91.
. Human Motion Capture with Scalable Body Models. . Universitat Politècnica de Catalunya (UPC); 2009. 
(13.45 MB)
(13.45 MB). Towards a Bayesian Approach to Robust Finding Correspondances in Multiple View Geometry Environments. In Computational Science – ICCS 2005. Berlin / Heidelberg: Springer; 2005. pp. 281–289.
. Head Orientation Estimation using Particle Filtering in Multiview Scenarios. In CLEAR'07 Second International Evaluation Workshop on Classification of Events, Activities and Relationships. 2007. pp. 1–11.
. 3D Human Action Recognition In Multiple View Scenarios. In 2ones Jornades UPC de Investigación en Automática, Visión y Robótica. 2006. pp. 1–5.
. Marker-based human motion capture in multi-view sequences. Eurasip journal on advances in signal processing. 2010;2010:1–11.
. From Pixels to Sentiment: Fine-tuning CNNs for Visual Sentiment Prediction. Image and Vision Computing. 2017;. (1.92 MB)
(1.92 MB). Sentiment concept embedding for visual affect recognition. In Multimodal Behavior Analysis in theWild. 1st ed. Elsevier; 2018.
. Learning to Skip State Updates in Recurrent Neural Networks. . 2017. (961.49 KB)
(961.49 KB). Skip RNN: Learning to Skip State Updates in Recurrent Neural Networks. In International Conference on Learning Representations (ICLR). 2018.
. Importance Weighted Evolution Strategies. In NeurIPS 2018 Deep Reinforcement Learning Workshop . Montreal, Quebec; 2018. (362.25 KB)
(362.25 KB). Explore, Discover and Learn: Unsupervised Discovery of State-Covering Skills. In International Conference on Machine Learning (ICML) 2020. 2020. (6.89 MB)
(6.89 MB). Diving Deep into Sentiment: Understanding Fine-tuned CNNs for Visual Sentiment Prediction. In 1st International Workshop on Affect and Sentiment in Multimedia. Brisbane, Australia: ACM; 2015. (506.22 KB)
(506.22 KB). Deep Learning that Scales: Leveraging Compute and Data. . Computer Architecture. [Barcelona, Catalonia]: Universitat Politècnica de Catalunya; 2020. (8.55 MB)
(8.55 MB). Layer-wise CNN Surgery for Visual Sentiment Prediction. . 2015. (1.51 MB)
(1.51 MB). Skip RNN: Learning to Skip State Updates in Recurrent Neural Networks. In NIPS Time Series Workshop 2017. Long Beach, CA, USA; 2017. (427.72 KB)
(427.72 KB). Distributed training strategies for a computer vision deep learning algorithm on a distributed GPU cluster. In International Conference on Computational Science (ICCS). Zurich, Switzerland: Elsevier; 2017. (576.67 KB)
(576.67 KB). SLAM-based 3D outdoor reconstructions from LIDAR data. In IC3D. Brussels, Belgium: IEEE; 2018. (3.21 MB)
(3.21 MB). Identifying brain ageing trajectories using variational autoencoders with regression model in neuroimaging data stratified by sex and validated against dementia-related risk factors. In 7th International Workshop on PRedictive Intelligence in MEdicine, MICCAI 2024. In Press.
. Information Theoretical Region Merging Approaches and Fusion of Hierarchical Image Segmentation Results. . Universitat Politècnica de Catalunya (UPC); 2010. (57.57 MB)
(57.57 MB). General Region Merging Based on First Order Markov Information Theory Statistical Measures. In 16th European Signal Processing Conference. 2008.
. Multiple view region matching using as a Lagrangian optimization problem. In 2007 International Conference on Acoustics, Speech and Signal Processing. 2007.
. Hierarchical fusion of color and depth information at partition level by cooperative region merging. In IEEE International Conference on Acoustics, Speech and Signal Processing 2009. 2009. pp. 973–976.
. Performance evaluation of probability density estimators for unsupervised information theoretical region merging. In 16th International Conference on Image Processing. 2009. pp. 4397–4400.