Self-supervised learning for autonomous vehicles perception: A conciliation between analytical and learning methods

Florent Chiaroni (1) , Mohamed-Cherif Rahal (2) , Nicolas Hueber (3) , Frédéric Dufaux (4)

1 L2S - Laboratoire des signaux et systèmes
2 VeDeCom - VEhicule DEcarboné et COmmuniquant et sa Mobilité
3 ISL - Institut franco-allemand de recherches de Saint-Louis
4 LTCI - Laboratoire Traitement et Communication de l'Information

Mots clés: Autonomous vehicle perception; self-supervised learning; semi-supervised learning; scene understanding

Domaines: Apprentissage [cs.LG]; Vision par ordinateur et reconnaissance de formes [cs.CV]; Machine Learning [stat.ML]; Intelligence artificielle [cs.AI]; Robotique [cs.RO]

Florent Chiaroni, Mohamed-Cherif Rahal, Nicolas Hueber, Frédéric Dufaux. Self-supervised learning for autonomous vehicles perception: A conciliation between analytical and learning methods. 2019. ⟨hal-02302705v1⟩