This work focuses on the automatic understanding of robotic and automotive scenes from monocular images. It aims to develop a 3D representation of the environment that facilitates the gradual emergence of object concepts. To achieve this, self-supervised learning methods incorporating physical and geometric constraints are employed, enabling these tasks to be performed without the need for annotations.