46 citations · 212 across the 15 of their papers we have counts for
19 papers
A Systematic Evaluation of Self-Supervised Learning for Label-Efficient Sleep Staging with Wearable EEG
Emilio Estevan, María Sierra-Torralba, Eduardo López-Larraz +1
Wearable EEG devices have emerged as a promising alternative to polysomnography (PSG). As affordable and scalable solutions, their widespread adoption results in the collection of…
Body Schema Acquisition through Active Learning
Ruben Martinez-Cantin, Manuel Lopes, Luis Montesano
We present an active learning algorithm for the problem of body schema learning, i.e. estimating a kinematic model of a serial robot. The learning process is done online using Recu…
Event Transformer+. A multi-purpose solution for efficient event data processing
Alberto Sabater, Luis Montesano, Ana C. Murillo
Event cameras record sparse illumination changes with high temporal resolution and high dynamic range. Thanks to their sparse recording and low consumption, they are increasingly u…
Event Transformer. A sparse-aware solution for efficient event data processing
Alberto Sabater, Luis Montesano, Ana C. Murillo
Event cameras are sensors of great interest for many applications that run in low-resource and challenging environments. They log sparse illumination changes with high temporal res…
Semi-Supervised Semantic Segmentation with Pixel-Level Contrastive Learning from a Class-wise Memory Bank
Inigo Alonso, Alberto Sabater, David Ferstl +2
This work presents a novel approach for semi-supervised semantic segmentation. The key element of this approach is our contrastive learning module that enforces the segmentation ne…
Domain and View-point Agnostic Hand Action Recognition
Alberto Sabater, Iñigo Alonso, Luis Montesano +1
Hand action recognition is a special case of action recognition with applications in human-robot interaction, virtual reality or life-logging systems. Building action classifiers a…
One-shot action recognition in challenging therapy scenarios
Alberto Sabater, Laura Santos, Jose Santos-Victor +3
One-shot action recognition aims to recognize new action categories from a single reference example, typically referred to as the anchor example. This work presents a novel approac…
Domain Adaptation in LiDAR Semantic Segmentation by Aligning Class Distributions
Inigo Alonso, Luis Riazuelo, Luis Montesano +1
LiDAR semantic segmentation provides 3D semantic information about the environment, an essential cue for intelligent systems during their decision making processes. Deep neural net…
Robust and efficient post-processing for video object detection
Alberto Sabater, Luis Montesano, Ana C. Murillo
Object recognition in video is an important task for plenty of applications, including autonomous driving perception, surveillance tasks, wearable devices or IoT networks. Object r…
Performance of object recognition in wearable videos
Alberto Sabater, Luis Montesano, Ana C. Murillo
Wearable technologies are enabling plenty of new applications of computer vision, from life logging to health assistance. Many of them are required to recognize the elements of int…
3D-MiniNet: Learning a 2D Representation from Point Clouds for Fast and Efficient 3D LIDAR Semantic Segmentation
Iñigo Alonso, Luis Riazuelo, Luis Montesano +1
LIDAR semantic segmentation, which assigns a semantic label to each 3D point measured by the LIDAR, is becoming an essential task for many robotic applications such as autonomous d…
CAM-Convs: Camera-Aware Multi-Scale Convolutions for Single-View Depth
Jose M. Facil, Benjamin Ummenhofer, Huizhong Zhou +3
Single-view depth estimation suffers from the problem that a network trained on images from one camera does not generalize to images taken with a different camera model. Thus, chan…
Condition-Invariant Multi-View Place Recognition
Jose M. Facil, Daniel Olid, Luis Montesano +1
Visual place recognition is particularly challenging when places suffer changes in its appearance. Such changes are indeed common, e.g., due to weather, night/day or seasons. In th…
Differentiating resting brain states using ordinal symbolic analysis
C. Quintero-Quiroz, Luis Montesano, A. J. Pons +3
Symbolic methods of analysis are valuable tools for investigating complex time-dependent signals. In particular, the ordinal method defines sequences of symbols according to the or…
Language Bootstrapping: Learning Word Meanings From Perception-Action Association
Giampiero Salvi, Luis Montesano, Alexandre Bernardino +1
We address the problem of bootstrapping language acquisition for an artificial system similarly to what is observed in experiments with human infants. Our method works by associati…
Single-View and Multi-View Depth Fusion
José M. Fácil, Alejo Concha, Luis Montesano +1
Dense and accurate 3D mapping from a monocular sequence is a key technology for several applications and still an open research area. This paper leverages recent results on single-…
Advantages of EEG phase patterns for the detection of gait intention in healthy and stroke subjects
Andreea Ioana Sburlea, Luis Montesano, Javier Minguez
One use of EEG-based brain-computer interfaces (BCIs) in rehabilitation is the detection of movement intention. In this paper we investigate for the first time the instantaneous ph…
Active Learning for Autonomous Intelligent Agents: Exploration, Curiosity, and Interaction
Manuel Lopes, Luis Montesano
In this survey we present different approaches that allow an intelligent agent to explore autonomous its environment to gather information and learn multiple tasks. Different commu…
On the Performance of Maximum Likelihood Inverse Reinforcement Learning
Héctor Ratia, Luis Montesano, Ruben Martinez-Cantin
Inverse reinforcement learning (IRL) addresses the problem of recovering a task description given a demonstration of the optimal policy used to solve such a task. The optimal polic…