Simultaneously Learning Corrections and Error Models for Geometry-based Visual Odometry Methods

Andrea De Maio, Simon Lacroix

This paper fosters the idea that deep learning methods can be used to complement classical visual odometry pipelines to improve their accuracy and to associate uncertainty models t…