Valeo.ai

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

Artificial intelligence is already at the core of the transformation of the automotive industry! 10 years ago, there was no real AI in cars. Today, most are packed with software, part of which is AI related. Artificial intelligence is changing mobility everywhere!

Valeo DRIVE4U® Sensors – Enabling autonomous driving in city centers

Multi-sensor perception

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.

Domain adaptation

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.

Uncertainty estimation

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

  • R&I Technical Engineer Florent Bartoccioni

    R&I Technical Engineer

    Perception | Scene understanding | Dynamic forecasting

    ENS Rennes | CTU Prague | INRIA

    Pragmatic dreamer

  • Research Scientist Alexandre Boulch

    Research Scientist

    Computer vision | Deep Learning | Geometry processing

    X | MVA | ENPC | ONERA

    3D perceiver

     

  • Senior Research Scientist Andrei Bursuc

    Senior Research Scientist

    Machine Learning | Computer Vision | Reliability | Self-supervised learning

    Politehnica | Mines | Inria | Safran

    Random walker

       

  • Research Scientist Mickaël Chen

    Research Scientist

    Generative Models | Forecasting

    Sorbonne Université

    Entropy producer

     

  • Principal scientist Matthieu Cord

    Principal scientist

    Deep Learning | Computer Vision | Vision and Language

    Enseirb | CergyU | KULeuven | Ensea | CNRS | SorbonneU | IUF

  • Research Scientist Spyros Gidaris

    Research Scientist

    Deep Learning | Computer Vision

    AUTH | Cortexica | ENPC

     

  • Research Scientist David Hurych

    Research Scientist

    Machine Learning | Computer Vision | Generative Networks

    CTU-Prague | NII-Tokyo

  • Principal scientist Renaud Marlet

    Principal scientist

    Computer Vision | Photogrammetry | Geometry Processing

    X | Inria | EdinburgU | Simulog | Inria | TrustedLogic | Inria | ENPC

     

  • Research Scientist Gilles Puy

    Research Scientist

    Deep Learning | Signal & Image Processing

    Supélec | EPFL | INRIA | Technicolor

     

  • Research Scientist Oriane Siméoni

    Research Scientist

    Computer vision | Deep Learning

    Enseirb | INRIA

      

  • Research scientist Tuan-Hung Vu

    Research scientist

    Deep Learning | Computer Vision

    Telecom | Inria | NEC

      

  • Research Scientist Eloi Zablocki

    Research Scientist

    Deep Learning | Computer Vision | Vision and Language

    X | MVA | SorbonneU

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