1 code implementation • 23 Apr 2021 • Pablo Martinez-Gonzalez, Sergiu Oprea, John Alejandro Castro-Vargas, Alberto Garcia-Garcia, Sergio Orts-Escolano, Jose Garcia-Rodriguez, Markus Vincze
Synthetic data generation has become essential in last years for feeding data-driven algorithms, which surpassed traditional techniques performance in almost every computer vision problem.
1 code implementation • 27 Mar 2021 • Sergiu Oprea, Giorgos Karvounas, Pablo Martinez-Gonzalez, Nikolaos Kyriazis, Sergio Orts-Escolano, Iason Oikonomidis, Alberto Garcia-Garcia, Aggeliki Tsoli, Jose Garcia-Rodriguez, Antonis Argyros
Relying on image-to-image translation, we improve the appearance of synthetic hands to approximate the statistical distribution underlying a collection of real images of hands.
no code implementations • 10 Apr 2020 • Sergiu Oprea, Pablo Martinez-Gonzalez, Alberto Garcia-Garcia, John Alejandro Castro-Vargas, Sergio Orts-Escolano, Jose Garcia-Rodriguez, Antonis Argyros
The ability to predict, anticipate and reason about future outcomes is a key component of intelligent decision-making systems.
no code implementations • 6 Mar 2020 • Victor Villena-Martinez, Sergiu Oprea, Marcelo Saval-Calvo, Jorge Azorin-Lopez, Andres Fuster-Guillo, Robert B. Fisher
Recent advancements in machine learning could be a turning point in these issues, particularly with the development of deep learning (DL) techniques, which are helping to improve multiple computer vision problems through an abstract understanding of the input data.
1 code implementation • 12 Mar 2019 • Sergiu Oprea, Pablo Martinez-Gonzalez, Alberto Garcia-Garcia, John Alejandro Castro-Vargas, Sergio Orts-Escolano, Jose Garcia-Rodriguez
On the other hand, for the quantitative evaluation a novel error metric has been proposed to visually analyze the performed grips.
1 code implementation • 19 Jan 2019 • Alberto Garcia-Garcia, Pablo Martinez-Gonzalez, Sergiu Oprea, John Alejandro Castro-Vargas, Sergio Orts-Escolano, Jose Garcia-Rodriguez, Alvaro Jover-Alvarez
Enter the RobotriX, an extremely photorealistic indoor dataset designed to enable the application of deep learning techniques to a wide variety of robotic vision problems.
2 code implementations • 16 Oct 2018 • Pablo Martinez-Gonzalez, Sergiu Oprea, Alberto Garcia-Garcia, Alvaro Jover-Alvarez, Sergio Orts-Escolano, Jose Garcia-Rodriguez
Gathering and annotating that sheer amount of data in the real world is a time-consuming and error-prone task.
2 code implementations • 22 Apr 2017 • Alberto Garcia-Garcia, Sergio Orts-Escolano, Sergiu Oprea, Victor Villena-Martinez, Jose Garcia-Rodriguez
This demand coincides with the rise of deep learning approaches in almost every field or application target related to computer vision, including semantic segmentation or scene understanding.