1 code implementation • 8 Dec 2023 • Daniel Rodriguez-Criado, Maria Chli, Luis J. Manso, George Vogiatzis
This paper introduces a novel methodology for bridging this `sim-real' gap by creating photorealistic images from 2D traffic simulations and recorded junction footage.
1 code implementation • 16 Dec 2022 • Daniel Rodriguez-Criado, Pilar Bachiller, George Vogiatzis, Luis J. Manso
Its numerous applications make multi-human 3D pose estimation a remarkably impactful area of research.
3 code implementations • 17 Feb 2021 • Pilar Bachiller, Daniel Rodriguez-Criado, Ronit R. Jorvekar, Pablo Bustos, Diego R. Faria, Luis J. Manso
This paper leverages Graph Neural Networks to model robot disruption considering the movement of the humans and the robot so that the model built can be used by path planning algorithms.
no code implementations • 10 Nov 2020 • Daniel Rodriguez-Criado, Pilar Bachiller, Luis J. Manso
Minimising the discomfort caused by robots when navigating in social situations is crucial for them to be accepted.
1 code implementation • 28 Jul 2020 • Daniel Rodriguez-Criado, Pilar Bachiller, Pablo Bustos, George Vogiatzis, Luis J. Manso
The proposal presented in this paper makes use of graph neural networks to merge the information acquired from multiple camera sources, achieving a mean absolute error below 125 mm for the location and 10 degrees for the orientation using low-resolution RGB images.