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Canton-Ferrer C, Sblendido R, Casas J, Pardàs M. Particle Filtering and Sparse Sampling for Multi-Person 3D Tracking. In IEEE International Conference on Image Processing. 2008. pp. 2644–2647.
Marqués F. Partition Coding Method and Device. International; 1999.
Marqués F, Gasull A. Partition coding using multigrid chain code and motion compensation. In IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING. 1996.
Marqués F, Gomila C, Gasull A. Partition Decoding Method and Device. International; 1999.
Pardàs M, Salembier P, Marqués F, Morros JR. Partition tree for a segmentation-based video coding system. In IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 1996. Atlanta (GA), USA; 1996. pp. 1982–1985.  (196.06 KB)
Marcotegui B, Marqués F, Wollborn M. Partition-based image representation as basis for user-assisted segmentation. In IEEE International Conference on Image Processing. 2000.
Assens M, McGuinness K, Giró-i-Nieto X, O'Connor N. PathGAN: Visual Scanpath Prediction with Generative Adversarial Networks. In ECCV 2018 Workshop on Egocentric Perception, Interaction and Compution (EPIC). Munich, Germany: Springer; 2018.  (3.78 MB)
Pinazo J, Lerín A, de Gibert FXavier, Moliner Á, Sevilla D, Jurado A, et al.. Perception in the era of Autonomous Vehicles. In Photonics 4 Smart Cities, SCEWC 2022. Barcelona: Photonics21; 2022.  (2.34 MB)
Dimiccoli M, Salembier P. Perceptual filtering with connected operators and image inpainting. In Proc. of International Symposium on Mathematical Morphology, ISMM 2007. Rio de Janeiro, Brazil; 2007. pp. 227–238.  (1.6 MB)
Ventosa S, Sayrol E, Vidal J. Perceptual mask estimation from watermarked images. In SPIE Electronic Imaging 2003. 2003. pp. 10–17.
Calderero F, Marqués F, Ortega A. Performance evaluation of probability density estimators for unsupervised information theoretical region merging. In 16th International Conference on Image Processing. 2009. pp. 4397–4400.
Bernardin K, Stiefelhagen R, Pnevmatikakis A, Lanz O, Brutti A, Casas J, et al.. Person Tracking. In Computers in the human interaction loop. London: Springer; 2009. pp. 11–22.
Bozal A. Personalized Image Classi cation from EEG Signals using Deep Learning. Giró-i-Nieto X. 2017.  (4.51 MB)
Podlipnik S, Hernandez C, Kiroglu A, García S, Ficapal J, Burgos J, et al.. Personalized medicine in melanoma patients aided by artificial intelligence. In Clinical Translation of Medical Image Computing and Computer Assisted Interventions (CLINICCAI) Workshop at MICCAI. 2021.
Manchon-Vizuete D, Gris-Sarabia I, Giró-i-Nieto X. Photo Clustering of Social Events by Extending PhotoTOC to a Rich Context. In ICMR 2014 Workshop on Social Events in Web Multimedia (SEWM). Glasgow, Scotland: ACM; 2014.  (1.66 MB)
Salvador J, Casas J. Photo-consistent surfaces from a sparse set of viewpoints. In 2010 IEEE International Conference on Image Processing. 2010. pp. 4045–4048.
Mas I, Morros JR, Vilaplana V. Picking groups instead of samples: A close look at Static Pool-based Meta-Active Learning. In ICCV Workshop - MDALC 2019. Seoul, South Korea; 2019.  (911.15 KB)
Nieto JJosé, Creus R, Giró-i-Nieto X. PiCoEDL: Discovery and Learning of Minecraft Navigation Goals from Pixels and Coordinates. In CVPR 2021 Embodied AI Workshop. 2021.  (847.54 KB)
LLadós J, Bou E, Bressan M, Sala O, Giró-i-Nieto X. The pillars of the Computer Vision Catalan Alliance. 2019.
Eugenio F, Marqués F, Marcello J. Pixel and sub-pixel accuracy in satellite image georeferencing using an automatic contour matching approach. In IEEE International Conference on Image Processing. 2001.
Creus R, Nieto JJosé, Giró-i-Nieto X. PixelEDL: Unsupervised Skill Discovery and Learning from Pixels. In CVPR 2021 Embodied AI Workshop. 2021.  (1.55 MB)
Puntí C. PixInPix: Hidding Pixels in Pixels. McGuinness K, Canton-Ferrer C, Giró-i-Nieto X. 2020.  (2.13 MB)
Geleta M, Puntí C, McGuinness K, Pons J, Canton-Ferrer C, Giró-i-Nieto X. PixInWav: Residual Steganography for Hiding Pixels in Audio. In ICASSP. 2022.  (5.77 MB)
Ramon E, Villar J, Ruiz G, Batard T, Giró-i-Nieto X. Plug-and-Train Loss for Model-Based Single View 3D Reconstruction. BMVA Technical Meeting: 3D vision with Deep Learning. London, UK: UPC; 2019.  (3.97 MB)
Alonso-González A, López-Martínez C, Salembier P. PolSAR speckle filtering and segmentation based on binary partition tree representation. In 5th International Workshop on Science and Applications of SAR Polarimetry and Polarimetric Interferometry, PolInSAR 2011. Frascati (Rome), Italy; 2011. pp. 1–19.  (11.09 MB)

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