336 citations · 595 across the 19 of their papers we have counts for
19 papers
Speeding up the annotation process in semantic segmentation industrial applications
Marta Fernandez-Moreno, Margarita Guerrero, Rosalia Rementeria +2
Current machine learning models commonly require large and well-annotated datasets. However, the annotation process often becomes a bottleneck, with increased complexity leading to…
A practical artificial intelligence framework for legal age estimation using clavicle computed tomography scans
Javier Venema, Stefano De Luca, Pablo Mesejo +1
Legal age estimation plays a critical role in forensic and medico-legal contexts, where decisions must be supported by accurate, robust, and reproducible methods with explicit unce…
A Novel Evolutionary Method for Automated Skull-Face Overlay in Computer-Aided Craniofacial Superimposition
Práxedes Martínez-Moreno, Andrea Valsecchi, Pablo Mesejo +3
Craniofacial Superimposition is a forensic technique for identifying skeletal remains by comparing a post-mortem skull with ante-mortem facial photographs. A critical step in this…
Towards a General Framework for HTN Modeling with LLMs
Israel Puerta-Merino, Carlos Núñez-Molina, Pablo Mesejo +1
The use of Large Language Models (LLMs) for generating Automated Planning (AP) models has been widely explored; however, their application to Hierarchical Planning (HP) is still fa…
Don't Forget your Inverse DDIM for Image Editing
Guillermo Gomez-Trenado, Pablo Mesejo, Oscar Cordón +1
The field of text-to-image generation has undergone significant advancements with the introduction of diffusion models. Nevertheless, the challenge of editing real images persists,…
A Roadmap to Guide the Integration of LLMs in Hierarchical Planning
Israel Puerta-Merino, Carlos Núñez-Molina, Pablo Mesejo +1
Recent advances in Large Language Models (LLMs) are fostering their integration into several reasoning-related fields, including Automated Planning (AP). However, their integration…
Towards a Unified Framework for Sequential Decision Making
Carlos Núñez-Molina, Pablo Mesejo, Juan Fernández-Olivares
In recent years, the integration of Automated Planning (AP) and Reinforcement Learning (RL) has seen a surge of interest. To perform this integration, a general framework for Seque…
On Using Admissible Bounds for Learning Forward Search Heuristics
Carlos Núñez-Molina, Masataro Asai, Pablo Mesejo +1
In recent years, there has been growing interest in utilizing modern machine learning techniques to learn heuristic functions for forward search algorithms. Despite this, there has…
A Review of Symbolic, Subsymbolic and Hybrid Methods for Sequential Decision Making
Carlos Núñez-Molina, Pablo Mesejo, Juan Fernández-Olivares
In the field of Sequential Decision Making (SDM), two paradigms have historically vied for supremacy: Automated Planning (AP) and Reinforcement Learning (RL). In the spirit of reco…
A Survey on Semi-Supervised Semantic Segmentation
Adrian Peláez-Vegas, Pablo Mesejo, Julián Luengo
Semantic segmentation is one of the most challenging tasks in computer vision. However, in many applications, a frequent obstacle is the lack of labeled images, due to the high cos…
NeSIG: A Neuro-Symbolic Method for Learning to Generate Planning Problems
Carlos Núñez-Molina, Pablo Mesejo, Juan Fernández-Olivares
In the field of Automated Planning there is often the need for a set of planning problems from a particular domain, e.g., to be used as training data for Machine Learning or as ben…
A Survey on Evolutionary Computation for Computer Vision and Image Analysis: Past, Present, and Future Trends
Ying Bi, Bing Xue, Pablo Mesejo +2
Computer vision (CV) is a big and important field in artificial intelligence covering a wide range of applications. Image analysis is a major task in CV aiming to extract, analyse…
Custom Structure Preservation in Face Aging
Guillermo Gomez-Trenado, Stéphane Lathuilière, Pablo Mesejo +1
In this work, we propose a novel architecture for face age editing that can produce structural modifications while maintaining relevant details present in the original image. We di…
Learning Visual Voice Activity Detection with an Automatically Annotated Dataset
Sylvain Guy, Stéphane Lathuilière, Pablo Mesejo +1
Visual voice activity detection (V-VAD) uses visual features to predict whether a person is speaking or not. V-VAD is useful whenever audio VAD (A-VAD) is inefficient either becaus…
Extended Gaze Following: Detecting Objects in Videos Beyond the Camera Field of View
Benoit Massé, Stéphane Lathuilière, Pablo Mesejo +1
In this paper we address the problems of detecting objects of interest in a video and of estimating their locations, solely from the gaze directions of people present in the video.…
Understanding Priors in Bayesian Neural Networks at the Unit Level
Mariia Vladimirova, Jakob Verbeek, Pablo Mesejo +1
We investigate deep Bayesian neural networks with Gaussian weight priors and a class of ReLU-like nonlinearities. Bayesian neural networks with Gaussian priors are well known to in…
DeepGUM: Learning Deep Robust Regression with a Gaussian-Uniform Mixture Model
Stéphane Lathuilière, Pablo Mesejo, Xavier Alameda-Pineda +1
In this paper, we address the problem of how to robustly train a ConvNet for regression, or deep robust regression. Traditionally, deep regression employs the L2 loss function, kno…
A Comprehensive Analysis of Deep Regression
Stéphane Lathuilière, Pablo Mesejo, Xavier Alameda-Pineda +1
Deep learning revolutionized data science, and recently its popularity has grown exponentially, as did the amount of papers employing deep networks. Vision tasks, such as human pos…
Neural Network Based Reinforcement Learning for Audio-Visual Gaze Control in Human-Robot Interaction
Stéphane Lathuilière, Benoit Massé, Pablo Mesejo +1
This paper introduces a novel neural network-based reinforcement learning approach for robot gaze control. Our approach enables a robot to learn and to adapt its gaze control strat…