Javier Ruiz Hidalgo

Biography

Javier Ruiz Hidalgo received a degree in Telecommunications Engineering at the Universitat Politècnica de Catalunya (UPC), Barcelona, Spain in 1997. From 1998 to 1999, he developed an MSc by Research on the field of Computer Vision by the University of East Anglia (UEA) in Norwich, UK. During 1999 he joined the Image Processing Group at UPC working on image and video indexing in the context of the MPEG-7 standard. In 2006, he received his PhD. in the field of image processing.

Since 1999 he has been involved in various European Projects as a researcher from the Image Processing Group at UPC. During 1999 and 2000 he worked in the ACTS(AC308) DICEMAN project developing new descriptors and representations for image and video sequences. Since 2001 he is also involved in the IST/FET(2000-26467) project MASCOT developing an efficient compression scheme exploiting metadata information. In 2009 he worked as principal researcher for the national project HESPERIA involved in improving the security of large infrastructures such as airports and power plants. From 2010 to 2013 he was principal researcher for the EU project FASCINATE working on interactive human computer interfaces using 3D data. During 2017 to 2021 he was the principal researcher for the national project MALEGRA developing tools combining graph signal representation and processing ideas with machine learning technology.

Since 2001 he is an Associate Professor at the Universitat Politècnica de Catalunya. He is currently lecturing on the area of digital signal and systems, image processing and computer vision. His current research interests include 3D video coding and analysis, graph neural networks, conditional generative networks and super-resolution.

Journal Articles top

2024
J. Gené-Mola, Ferrer-Ferrer, M., Hemming, J., Dalfsen, P., Hoog, D., Sanz-Cortiella, R., Rosell-Polo, J. R., Morros, J. R., Vilaplana, V., Ruiz-Hidalgo, J., and Gregorio, E., AmodalAppleSize_RGB-D dataset: RGB-D images of apple trees annotated with modal and amodal segmentation masks for fruit detection, visibility and size estimation, Data in Brief, vol. 52, 2024.
2023
M. Ferrer-Ferrer, Ruiz-Hidalgo, J., Gregorio, E., Vilaplana, V., Morros, J. R., and Gené-Mola, J., Simultaneous Fruit Detection and Size Estimation Using Multitask Deep Neural Networks  , Biosystems Engineering, vol. 233, pp. 63-75, 2023. (10.36 MB)
J. Gené-Mola, Ferrer-Ferrer, M., Gregorio, E., Blok, P. M., Hemming, J., Morros, J. R., Rosell-Polo, J. R., Vilaplana, V., and Ruiz-Hidalgo, J., Looking behind occlusions: A study on amodal segmentation for robust on-tree apple fruit size estimation, Computers and Electronics in Agriculture, vol. 209, 2023. (9.02 MB)
2021
A. Mosella-Montoro and Ruiz-Hidalgo, J., 2D–3D Geometric Fusion network using Multi-Neighbourhood Graph Convolution for RGB-D indoor scene classification, Information Fusion, vol. 76, 2021. (771.86 KB)
2020
J. Gené-Mola, Sanz, R., Rosell-Polo, J. R., Morros, J. R., Ruiz-Hidalgo, J., Vilaplana, V., and Gregorio, E., Fruit detection and 3D location using instance segmentation neural networks and structure-from-motion photogrammetry, Computers and Electronics in Agriculture, vol. 169, 2020.

Book Chapters and Bookstop

Conference Papers top

2023
C. Hurtado, Shekkizhar, S., Ruiz-Hidalgo, J., and Ortega, A., Study of Manifold Geometry using Multiscale Non-Negative Kernel Graphs, in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Rhodes Island, Greece, 2023. (1.4 MB)
J. Gené-Mola, Felip-Pomés, M., Net-Barnés, F., Morros, J. R., Miranda, J. C., J. Satorra, A., L. Jones, A., J. Sanahuja, L., Ruiz-Hidalgo, J., and Gregorio, E., Video-Based Fruit Detection and Tracking for Apple Counting and Mapping, in IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor), 2023. (680.49 KB)
2022
D. Bonet, Ortega, A., Ruiz-Hidalgo, J., and Shekkizhar, S., Channel Redundancy and Overlap in Convolutional Neural Networks with Channel-Wise NNK Graphs, in International Conference on Acoustics, Speech and Signal Processing, 2022. (1.13 MB)
A. Mosella-Montoro and Ruiz-Hidalgo, J., SkinningNet: Two-Stream Graph Convolutional Neural Network for Skinning Prediction of Synthetic Characters, in IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR), New Orleans, USA, 2022. (5.45 MB)
2021
D. Bonet, Ortega, A., Ruiz-Hidalgo, J., and Shekkizhar, S., Channel-Wise Early Stopping without a Validation Set via NNK Polytope Interpolation, in Asia Pacific Signal and Information Processing Association Annual Summit, APSIPA, Tokyo, Japan, 2021. (995.84 KB)

Theses top

2023
A. Mosella-Montoro, Graph Convolutional Neural Networks for 3D Data Analysis, Universitat Politècnica de Catalunya, Barcelona, 2023.
2020
A. Pujol-Miró, Learning to extract features for 2D-3D multimodal registration, Universitat Politècnica de Catalunya (UPC), 2020. (14.22 MB)
2017
E. Perez-Pellitero, Manifold Learning for Super Resolution, Leibniz Universität Hannover, Hannover, 2017. (18.6 MB)
M. Maceira, Multi-view depth coding based on a region representation combining color and depth information, Universitat Politècnica de Catalunya (UPC), 2017. (15.24 MB)
2013
X. Suau, Human body analysis using depth data, Universitat Politècnica de Catalunya (UPC), 2013. (10.67 MB)

Research Areas top

Region-based image and video processing Internal Jan
1992
Dec
2020
Multiview Coding Internal Jul
2010
Jul
2018
Multi-view/Multi-sensor scene capture, analysis and representation Internal Mar
2004
Nov
2015