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Canton-Ferrer C. Human Motion Capture with Scalable Body Models. Casas J, Pardàs M. Universitat Politècnica de Catalunya (UPC); 2009.  (13.45 MB)
Canton-Ferrer C, Casas J, Pardàs M. Head Orientation Estimation Using Particle Filtering in Multiview Scenarios. In Multimodal Technologies for Perception of Humans. Berlin / Heidelberg: Springer; 2008. pp. 317–327.
Canton-Ferrer C, Segura C, Pardàs M, Casas J, Hernando J. Multimodal Real-Time Focus of Attention Estimation in SmartRooms. In CVPR 2008 Workshop on Human Communicative Behavior Analysis. 2008. pp. 1–4.
Canton-Ferrer C, Casas J, Pardàs M. Real-time 3D multi-person tracking using Monte Carlo surface sampling. In 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops. 2010. pp. 40–46.
Canton-Ferrer C, Casas J, Tekalp M, Pardàs M. Projective Kalman Filter: Multiocular Tracking of 3D Locations Towards Scene Understanding. In Machine Learning for Multimodal Interaction. Berlin / Heidelberg: Springer; 2006. pp. 250–261.
Canton-Ferrer C, Canton-Ferrer C, Casas J, Pardàs M. Fusion of multiple viewpoint information towards 3d face robust orientation detection. In IEEE International Conference on Image Processing. 2005.
Canton-Ferrer C, Casas J, Pardàs M. Head Pose Detection based on Fusion of Multiple Viewpoint Information. In CLEAR'06 Evaluation Campaign and Workshop - Classification of Events, Activities and Relationships. 2006. pp. 305–310.
Canton-Ferrer C, Casas J, Pardàs M, Monte E. Multi-camera multi-object voxel-based Monte Carlo 3D tracking strategies. Eurasip journal on advances in signal processing. 2011;2011:1–15.
Canton-Ferrer C, Casas J, Pardàs M. Spatio-temporal alignment and hyperspherical radon transform for 3D gait recognition in multi-view environments. In 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops. 2010. pp. 116–121.
Canton-Ferrer C, Casas J, Pardàs M. 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.
Canton-Ferrer C, Canton-Ferrer C, Casas J, Pardàs M. Towards a bayesian approach to robust finding correspondances in multiple view geometry environments. In Workshop on Computer Graphics and Geometric Modelling. Intrernational Conference on Computational Science. 2005. pp. 281–289.
Cànaves MArtigues. Prevention of Alzheimer's Disease: a contribution from MRI and machine learning. Petrone P, Vilaplana V. 2018.
Campos V. Layer-wise CNN Surgery for Visual Sentiment Prediction. Salvador A, Jou B, Giró-i-Nieto X. 2015.  (1.51 MB)
Campos V. Deep Learning that Scales: Leveraging Compute and Data. Torres J, Giró-i-Nieto X. Computer Architecture. [Barcelona, Catalonia]: Universitat Politècnica de Catalunya; 2020.  (8.55 MB)
Campos V, Jou B, Giró-i-Nieto X, Torres J, Chang S-F. 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)
Campos V. Learning to Skip State Updates in Recurrent Neural Networks. Jou B, Chang S-F, Giró-i-Nieto X. 2017.  (961.49 KB)
Campos V, Sastre F, Yagües M, Bellver M, Giró-i-Nieto X, Torres J. 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)
Campos V, Giró-i-Nieto X, Jou B, Torres J, Chang S-F. Sentiment concept embedding for visual affect recognition. In Multimodal Behavior Analysis in theWild. 1st ed. Elsevier; 2018.
Campos V, Salvador A, Giró-i-Nieto X, Jou B. 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)
Campos V, Giró-i-Nieto X, Torres J. Importance Weighted Evolution Strategies. In NeurIPS 2018 Deep Reinforcement Learning Workshop . Montreal, Quebec; 2018.  (362.25 KB)
Campos V, Jou B, Giró-i-Nieto X. From Pixels to Sentiment: Fine-tuning CNNs for Visual Sentiment Prediction. Image and Vision Computing. 2017;.  (1.92 MB)
Campos V, Trott A, Xiong C, Socher R, Giró-i-Nieto X, Torres J. Explore, Discover and Learn: Unsupervised Discovery of State-Covering Skills. In International Conference on Machine Learning (ICML) 2020. 2020.  (6.89 MB)
Campos V, Jou B, Giró-i-Nieto X, Torres J, Chang S-F. Skip RNN: Learning to Skip State Updates in Recurrent Neural Networks. In International Conference on Learning Representations (ICLR). 2018.
Caminal I, Casas J, Royo S. SLAM-based 3D outdoor reconstructions from LIDAR data. In IC3D. Brussels, Belgium: IEEE; 2018.  (3.21 MB)
Calderero F, Marqués F. Region merging parameter dependency as information diversity to create sparse hierarchies of partitions. In 2010 IEEE International Conference on Image Processing. 2010. pp. 2237–2240.

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