no code implementations • 5 Apr 2024 • Paola Natalia Cañas, Mikel García, Nerea Aranjuelo, Marcos Nieto, Aitor Iglesias, Igor Rodríguez
This paper describes the methodology for building a dynamic risk assessment for ADAS (Advanced Driving Assistance Systems) algorithms in parking scenarios, fusing exterior and interior perception for a better understanding of the scene and a more comprehensive risk estimation.
no code implementations • 11 Jan 2024 • Pablo Alonso, Jon Ander Iñiguez de Gordoa, Juan Diego Ortega, Sara García, Francisco Javier Iriarte, Marcos Nieto
Runway and taxiway pavements are exposed to high stress during their projected lifetime, which inevitably leads to a decrease in their condition over time.
no code implementations • 1 Dec 2023 • Jose Luis Apellániz, Mikel García, Nerea Aranjuelo, Javier Barandiarán, Marcos Nieto
First, our approach detects the curbs at each scan using a segmentation deep neural network.
no code implementations • 13 May 2022 • Paola Natalia Canas, Juan Diego Ortega, Marcos Nieto, Oihana Otaegui
Strategies that include the generation of synthetic data are beginning to be viable as obtaining real data can be logistically complicated, very expensive or slow.
no code implementations • 13 May 2022 • Marcos Nieto, Mikel Garcia, Itziar Urbieta, Oihana Otaegui
Work on Local Dynamic Maps (LDM) implementation is still in its early stages, as the LDM standards only define how information shall be structured in databases, while the mechanism to fuse or link information across different layers is left undefined.
no code implementations • 13 Apr 2022 • Gorka Velez, Edoardo Bonetto, Daniele Brevi, Angel Martin, Gianluca Rizzi, Oscar Castañeda, Arslane Hamza Cherif, Marcos Nieto, Oihana Otaegui
Cars capture and generate huge volumes of data in real-time about the driving dynamics, the environment, and the driver and passengers' activities.
no code implementations • 29 Jun 2021 • Fadi Boutros, Naser Damer, Jan Niklas Kolf, Kiran Raja, Florian Kirchbuchner, Raghavendra Ramachandra, Arjan Kuijper, Pengcheng Fang, Chao Zhang, Fei Wang, David Montero, Naiara Aginako, Basilio Sierra, Marcos Nieto, Mustafa Ekrem Erakin, Ugur Demir, Hazim Kemal, Ekenel, Asaki Kataoka, Kohei Ichikawa, Shizuma Kubo, Jie Zhang, Mingjie He, Dan Han, Shiguang Shan, Klemen Grm, Vitomir Štruc, Sachith Seneviratne, Nuran Kasthuriarachchi, Sanka Rasnayaka, Pedro C. Neto, Ana F. Sequeira, Joao Ribeiro Pinto, Mohsen Saffari, Jaime S. Cardoso
These teams successfully submitted 18 valid solutions.
no code implementations • 20 Apr 2021 • David Montero, Marcos Nieto, Peter Leskovsky, Naiara Aginako
Experimental results show that the proposed approach highly boosts the original model accuracy when dealing with masked faces, while preserving almost the same accuracy on the original non-masked datasets.
no code implementations • 31 Mar 2021 • David Montero, Naiara Aginako, Basilio Sierra, Marcos Nieto
In this work, we address the problem of large-scale online face clustering: given a continuous stream of unknown faces, create a database grouping the incoming faces by their identity.
no code implementations • 27 Aug 2020 • Juan Diego Ortega, Neslihan Kose, Paola Cañas, Min-An Chao, Alexander Unnervik, Marcos Nieto, Oihana Otaegui, Luis Salgado
Vision is the richest and most cost-effective technology for Driver Monitoring Systems (DMS), especially after the recent success of Deep Learning (DL) methods.
1 code implementation • 2 Mar 2020 • Guus Engels, Nerea Aranjuelo, Ignacio Arganda-Carreras, Marcos Nieto, Oihana Otaegui
Top view images are generated from point clouds as input for the networks.