Federico Alvarez
Technical University of Madrid
104 Papers
372 Citations
Federico Alvarez is an academic researcher from Technical University of Madrid. The author has contributed to research in topics: Computer science & The Internet. The author has an hindex of 17, co-authored 97 publications. Previous affiliations of Federico Alvarez include Polytechnic University of Puerto Rico.
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Papers
An Edge-to-Cloud Virtualized Multimedia Service Platform for 5G Networks
Federico Alvarez,David Breitgand,David Griffin,Pasquale Andriani,Stamatia Rizou,Nikolaos Zioulis,Francesca Moscatelli,Javier Serrano,Madeleine Keltsch,Panagiotis Trakadas,T. Khoa Phan,Avi Weit,Ugur Acar,Oscar Prieto,Francesco Iadanza,Gino Carrozzo,Harilaos Koumaras,Dimitrios Zarpalas,David Jimenez +18 more
TL;DR: The preliminary results of the 5G-MEDIA SVP platform evaluation are compared against current practice and show that the proposed platform provides enhanced functionality for the operators and infrastructure owners, while ensuring better NS performance to service providers and end users.
Spherical View Synthesis for Self-Supervised 360° Depth Estimation
Nikolaos Zioulis,Antonis Karakottas,Dimitrios Zarpalas,Federico Alvarez,Petros Daras +4 more
- 01 Sep 2019
TL;DR: In this article, the authors explore spherical view synthesis for learning monocular 360 depth in a self-supervised manner and demonstrate its feasibility for horizontal and vertical baselines, as well as for the trinocular case.
SWiBluX: Multi-Sensor Deep Learning Fingerprint for Precise Real-Time Indoor Tracking
Alberto Belmonte-Hernandez,Gustavo Hernandez-Penaloza,David Martin Gutierrez,Federico Alvarez +3 more
TL;DR: A novel multi-modal complete tracking system, called SWiBluX, based on statistic and DL techniques is presented, which relies on relevant feature extraction from available data sources to estimate user’s/target indoor position using a multi-phase statistical Fingerprint and DL disruptive approach.
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Pano3D: A Holistic Benchmark and a Solid Baseline for 360° Depth Estimation
Georgios Albanis,Nikolaos Zioulis,Petros Drakoulis,Vasileios Gkitsas,Vladimiros Sterzentsenko,Federico Alvarez,Dimitrios Zarpalas,Petros Daras +7 more
- 19 Jun 2021
TL;DR: By disentangling the capacity to generalize in unseen data into different test splits, Pano3D represents a holistic benchmark for 360o depth estimation and results into a solid baseline for panoramic depth that followup works can built upon to steer future progress.
A Deep Learning Approach for Robust Detection of Bots in Twitter Using Transformers
David Martin-Gutierrez,Gustavo Hernandez-Penaloza,Alberto Hernandez,Alicia Lozano-Diez,Federico Alvarez +4 more
TL;DR: In this article, a multilingual approach for addressing the bot identification task in Twitter via deep learning (DL) approaches to support end-users when checking the credibility of a certain Twitter account.