Pedro P. B. de Gusmão — accepted AI-conference papers

2021

RadarLoc: Learning to Relocalize in FMCW Radar

Wei Wang, Pedro P. B. de Gusmão, Bo Yang, Andrew Markham, Niki Trigoni

ICRA 2021poster

Relocalization is a fundamental task in the field of robotics and computer vision. There is considerable work in the field of deep camera relocalization, which directly estimates poses from raw images. However, learning-based methods have not yet been applied to the radar sensory data. In this work,…

Cited by 28 Source ↗Scholar ↗

2019

GANVO: Unsupervised Deep Monocular Visual Odometry and Depth Estimation with Generative Adversarial Networks

Yasin Almalioglu, Muhamad Risqi U. Saputra, Pedro P. B. de Gusmão, Andrew Markham, Niki Trigoni

ICRA 2019poster

In the last decade, supervised deep learning approaches have been extensively employed in visual odometry (VO) applications, which is not feasible in environments where labelled data is not abundant. On the other hand, unsupervised deep learning approaches for localization and mapping in unknown env…

Cited by 199 Source ↗Scholar ↗