Adrien Gaidon: Self supervised 3 D vision

Is one eye all you need Can we learn robot perception from raw videos only Can we get robust 3D depth estimation from a single monocular camera In this talk, we will discuss recent research progress we made at TRI on selfsupervised learning for monocular 3D vision, its uses, limitations, and promising future directions combining selfsupervision with other scalable sources of supervision. Adrien Gaidon is the Head of Machine Learning Research at the Toyota Research Institute (TRI) in Los Altos, CA, USA. Adriens research focuses on scaling up ML for robot autonomy, spanning Scene and Behavior Understanding, Simulation for Deep Learning, 3D Computer Vision, and SelfSupervised Learning. He received his PhD from Microsoft Research Inria Paris in 2012, has over 50 publications and patents in ML, CV, AI, top entries in international Computer Vision competitions, multiple best reviewer awards, international press coverage for his work on Deep Learning with simulation, was a guest editor for the International