14 citations · 44 across the 10 of their papers we have counts for
10 papers
Neural Style Transfer with Twin-Delayed DDPG for Shared Control of Robotic Manipulators
Raul Fernandez-Fernandez, Marco Aggravi, Paolo Robuffo Giordano +2
Neural Style Transfer (NST) refers to a class of algorithms able to manipulate an element, most often images, to adopt the appearance or style of another one. Each element is defin…
Real Evaluations Tractability using Continuous Goal-Directed Actions in Smart City Applications
Raul Fernandez-Fernandez, Juan G. Victores, David Estevez +1
One of the most important challenges of Smart City Applications is to adapt the system to interact with non-expert users. Robot imitation frameworks aim to simplify and reduce time…
Neural Policy Style Transfer
Raul Fernandez-Fernandez, Juan G. Victores, Jennifer J. Gago +2
Style Transfer has been proposed in a number of fields: fine arts, natural language processing, and fixed trajectories. We scale this concept up to control policies within a Deep R…
Deep Robot Sketching: An application of Deep Q-Learning Networks for human-like sketching
Raul Fernandez-Fernandez, Juan G. Victores, Carlos Balaguer
The current success of Reinforcement Learning algorithms for its performance in complex environments has inspired many recent theoretical approaches to cognitive science. Artistic…
Transferring human emotions to robot motions using Neural Policy Style Transfer
Raul Fernandez-Fernandez, Bartek Łukawski, Juan G. Victores +1
Neural Style Transfer (NST) was originally proposed to use feature extraction capabilities of Neural Networks as a way to perform Style Transfer with images. Pre-trained image clas…
Sequence-to-Sequence Natural Language to Humanoid Robot Sign Language
Jennifer J. Gago, Valentina Vasco, Bartek Łukawski +4
This paper presents a study on natural language to sign language translation with human-robot interaction application purposes. By means of the presented methodology, the humanoid…
Quick, Stat!: A Statistical Analysis of the Quick, Draw! Dataset
Raul Fernandez-Fernandez, Juan G. Victores, David Estevez +1
The Quick, Draw! Dataset is a Google dataset with a collection of 50 million drawings, divided in 345 categories, collected from the users of the game Quick, Draw!. In contrast wit…
Sign Language Representation by TEO Humanoid Robot: End-User Interest, Comprehension and Satisfaction
Jennifer J. Gago, Juan G. Victores, Carlos Balaguer
In this paper, we illustrate our work on improving the accessibility of Cyber-Physical Systems (CPS), presenting a study on human-robot interaction where the end-users are either d…
Robot Imitation through Vision, Kinesthetic and Force Features with Online Adaptation to Changing Environments
Raul Fernandez-Fernandez, Juan G. Victores, David Estevez +1
Continuous Goal-Directed Actions (CGDA) is a robot imitation framework that encodes actions as the changes they produce on the environment. While it presents numerous advantages wi…
Robotic Ironing with 3D Perception and Force/Torque Feedback in Household Environments
David Estevez, Juan G. Victores, Raul Fernandez-Fernandez +1
As robotic systems become more popular in household environments, the complexity of required tasks also increases. In this work we focus on a domestic chore deemed dull by a majori…