In this work we propose a deep learning pipeline to predict the visual future appearance of an urban scene.
An Image Completion Network (ICN) is then trained to generate a realistic image starting from this geometric guidance.
Multi-People Tracking in an open-world setting requires a special effort in precise detection.
Awareness of the road scene is an essential component for both autonomous vehicles and Advances Driver Assistance Systems and is gaining importance both for the academia and car companies.
Despite the advent of autonomous cars, it's likely - at least in the near future - that human attention will still maintain a central role as a guarantee in terms of legal responsibility during the driving task.
We provide a distribution-free test that can be used to determine whether any two joint distributions $p$ and $q$ are statistically different by inspection of a large enough set of samples.