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We are building an artificial intelligence research center for automotive applications based in the center of Paris, a project started in 2017 to conduct ambitious research projects, regarding assisted and autonomous driving
Automated driving relies first on a diverse range of sensors, like Valeo’s cameras, LiDARs, radars and ultrasonics. Exploiting at best the outputs of each of these sensors at any instant is fundamental to understand the complex environment of the vehicle. To this end, we explore various deep learning approaches where sensors are considered both in isolation and collectively.
Deep learning and reinforcement learning are key technologies for autonomous driving. One of the challenges they face is to adapt to conditions which differ from those met during training. To improve systems’ performance in such situations, we explore so-called domain adaption techniques, as in AdvEnt, our project presented at CVPR 2019.
When the unexpected happens, when the weather badly degrades, when a sensor gets blocked, the embarked perception system should diagnose the situation and react accordingly, e.g, by calling an alternative system or the human driver. With this in mind, we investigate automatic ways to assess the uncertainty of a system and to predict its performance.
Meet our team
Deep Learning | Vision and Language | Visual reasoning