118 citations · 120 across the 5 of their papers we have counts for
5 papers
Occlusion-aware Driver Monitoring System using the Driver Monitoring Dataset
Paola Natalia Cañas, Alexander Diez, David Galvañ +2
This paper presents a robust, occlusion-aware driver monitoring system (DMS) utilizing the Driver Monitoring Dataset (DMD). The system performs driver identification, gaze estimati…
Exploration of VLMs for Driver Monitoring Systems Applications
Paola Natalia Cañas, Marcos Nieto, Oihana Otaegui +1
In recent years, we have witnessed significant progress in emerging deep learning models, particularly Large Language Models (LLMs) and Vision-Language Models (VLMs). These models…
Dynamic Risk Assessment Methodology with an LDM-based System for Parking Scenarios
Paola Natalia Cañas, Mikel García, Nerea Aranjuelo +3
This paper describes the methodology for building a dynamic risk assessment for ADAS (Advanced Driving Assistance Systems) algorithms in parking scenarios, fusing exterior and inte…
Virtual passengers for real car solutions: synthetic datasets
Paola Natalia Canas, Juan Diego Ortega, Marcos Nieto +1
Strategies that include the generation of synthetic data are beginning to be viable as obtaining real data can be logistically complicated, very expensive or slow. Not only the cap…
DMD: A Large-Scale Multi-Modal Driver Monitoring Dataset for Attention and Alertness Analysis
Juan Diego Ortega, Neslihan Kose, Paola Cañas +5
Vision is the richest and most cost-effective technology for Driver Monitoring Systems (DMS), especially after the recent success of Deep Learning (DL) methods. The lack of suffici…