1 code implementation • 1 Jul 2020 • Alessandro Simoni, Luca Bergamini, Andrea Palazzi, Simone Calderara, Rita Cucchiara
In this work we propose a deep learning pipeline to predict the visual future appearance of an urban scene.
1 code implementation • 24 Jul 2019 • Andrea Palazzi, Luca Bergamini, Simone Calderara, Rita Cucchiara
An Image Completion Network (ICN) is then trained to generate a realistic image starting from this geometric guidance.
2 code implementations • ECCV 2018 • Matteo Fabbri, Fabio Lanzi, Simone Calderara, Andrea Palazzi, Roberto Vezzani, Rita Cucchiara
Multi-People Tracking in an open-world setting requires a special effort in precise detection.
3 code implementations • 26 Jun 2017 • Andrea Palazzi, Guido Borghi, Davide Abati, Simone Calderara, Rita Cucchiara
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.
1 code implementation • 10 May 2017 • Andrea Palazzi, Davide Abati, Simone Calderara, Francesco Solera, Rita Cucchiara
In this work we aim to predict the driver's focus of attention.
1 code implementation • 24 Nov 2016 • Andrea Palazzi, Francesco Solera, Simone Calderara, Stefano Alletto, Rita Cucchiara
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.
no code implementations • 25 Jul 2016 • Francesco Solera, Andrea Palazzi
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.