Javier Rodriguez Puigvert

Bayesian Deep Neural Networks for Supervised Learning of Single-View Depth

Uncertainty quantification is essential for robotic perception, as overconfident or point estimators can lead to collisions and damages to the environment and the robot. In this letter, we evaluate scalable approaches to uncertainty quantification in single-view supervised depth learning, specifical