Human Driving Focus
Human driving focus research investigates how attention is directed during driving tasks, aiming to improve driver assistance systems and autonomous vehicle safety. Current research emphasizes developing models that efficiently process visual information, often employing transformer architectures, convolutional neural networks, and recurrent neural networks to achieve accurate object detection, scene understanding, and action prediction. This work is significant for enhancing the reliability and safety of both human-driven and autonomous vehicles by improving perception and decision-making capabilities in complex driving scenarios.
Papers
FOCUS: Effective Embedding Initialization for Monolingual Specialization of Multilingual Models
Konstantin Dobler, Gerard de Melo
SMT 2.0: A Surrogate Modeling Toolbox with a focus on Hierarchical and Mixed Variables Gaussian Processes
Paul Saves, Remi Lafage, Nathalie Bartoli, Youssef Diouane, Jasper Bussemaker, Thierry Lefebvre, John T. Hwang, Joseph Morlier, Joaquim R. R. A. Martins