43 citations · 107 across the 13 of their papers we have counts for
14 papers
Neural Networks Assisted Metropolis-Hastings for Bayesian Estimation of Critical Exponent on Elliptic Black Hole Solution in 4D Using Quantum Perturbation Theory
Armin Hatefi, Ehsan Hatefi, Roberto J. Lopez-Sastre
It is well-known that the critical gravitational collapse produces continuous self-similar solutions characterized by the Choptuik critical exponent, . We examine the solutions…
Modeling the complexity of Elliptic Black Hole Solution In 4D Using Hamiltonian Monte Carlo with Stacked Neural Networks
Armin Hatefi, Ehsan Hatefi, Roberto J. López-Sastre
In this paper, we study the black hole solution of self-similar gravitational collapse in the Einstein-axion-dilaton system for the elliptic class in four dimensions. The solution…
Rethinking Online Action Detection in Untrimmed Videos: A Novel Online Evaluation Protocol
Marcos Baptista Rios, Roberto J. López-Sastre, Fabian Caba Heilbron +3
The Online Action Detection (OAD) problem needs to be revisited. Unlike traditional offline action detection approaches, where the evaluation metrics are clear and well established…
The Instantaneous Accuracy: a Novel Metric for the Problem of Online Human Behaviour Recognition in Untrimmed Videos
Marcos Baptista Rios, Roberto J. López-Sastre, Fabian Caba Heilbron +3
The problem of Online Human Behaviour Recognition in untrimmed videos, aka Online Action Detection (OAD), needs to be revisited. Unlike traditional offline action detection approac…
Deep Anomaly Detection for Generalized Face Anti-Spoofing
Daniel Pérez-Cabo, David Jiménez-Cabello, Artur Costa-Pazo +1
Face recognition has achieved unprecedented results, surpassing human capabilities in certain scenarios. However, these automatic solutions are not ready for production because the…
Generalized Presentation Attack Detection: a face anti-spoofing evaluation proposal
Artur Costa-Pazo, David Jimenez-Cabello, Esteban Vazquez-Fernandez +2
Over the past few years, Presentation Attack Detection (PAD) has become a fundamental part of facial recognition systems. Although much effort has been devoted to anti-spoofing res…
Embarrassingly Simple Model for Early Action Proposal
Marcos Baptista-Ríos, Roberto J. López-Sastre, Franciso Javier Acevedo-Rodríguez +1
Early action proposal consists in generating high quality candidate temporal segments that are likely to contain an action in a video stream, as soon as they happen. Many sophistic…
ISA: Intelligent Speed Adaptation from Appearance
Carlos Herranz-Perdiguero, Roberto J. López-Sastre
In this work we introduce a new problem named Intelligent Speed Adaptation from Appearance (ISA). Technically, the goal of an ISA model is to predict for a given image of a…
In pixels we trust: From Pixel Labeling to Object Localization and Scene Categorization
Carlos Herranz-Perdiguero, Carolina Redondo-Cabrera, Roberto J. López-Sastre
While there has been significant progress in solving the problems of image pixel labeling, object detection and scene classification, existing approaches normally address them sepa…
Learning Short-Cut Connections for Object Counting
Daniel Oñoro-Rubio, Mathias Niepert, Roberto J. López-Sastre
Object counting is an important task in computer vision due to its growing demand in applications such as traffic monitoring or surveillance. In this paper, we consider object coun…
Learning to Exploit the Prior Network Knowledge for Weakly-Supervised Semantic Segmentation
Carolina Redondo-Cabrera, Marcos Baptista-Ríos, Roberto J. López-Sastre
Training a Convolutional Neural Network (CNN) for semantic segmentation typically requires to collect a large amount of accurate pixel-level annotations, a hard and expensive task.…
The challenge of simultaneous object detection and pose estimation: a comparative study
Daniel Oñoro-Rubio, Roberto J. López-Sastre, Carolina Redondo-Cabrera +1
Detecting objects and estimating their pose remains as one of the major challenges of the computer vision research community. There exists a compromise between localizing the objec…
Unsupervised learning from videos using temporal coherency deep networks
Carolina Redondo-Cabrera, Roberto J. López-Sastre
In this work we address the challenging problem of unsupervised learning from videos. Existing methods utilize the spatio-temporal continuity in contiguous video frames as regulari…
Answering Visual-Relational Queries in Web-Extracted Knowledge Graphs
Daniel Oñoro-Rubio, Mathias Niepert, Alberto García-Durán +2
A visual-relational knowledge graph (KG) is a multi-relational graph whose entities are associated with images. We explore novel machine learning approaches for answering visual-re…