The event is free of charge. Limited seats.
Registration will be open until capacity limit is reached. A confirmation e-mail will be sent out afterwards.
-- Schedule --
6:30 PM: Reception (please register w/ your full name in the registration form above)
7:00 PM: Welcome and Introduction to TRI/TRI-AD by David Garber (Product Manager, TRI) and Yusuke Yachide (Tech Lead, TRI-AD)
7:20 PM: Introduction of Engineering team in TRI-AD by Yuki Oyama (Assistant Manager, Human Resources, TRI-AD)
7:30 PM: Tech Talk: Beyond Supervised Driving by Adrien Gaidon (ML Lead, TRI)
8:00 PM: Automated Driving Panel Discussion and general Q&A by Suzana Ilić (MLT), David Garber, Adrien Gaidon, Yusuke Yachide, and others
8:30 PM: Interactive Sessions and Networking
9:30 PM: End of Event
-- Tech Talk Details: Beyond Supervised Driving --
-- Abstract --
Crowd-sourced steering does not sound as appealing as automated driving. We need to go beyond supervised learning for automated driving, including for computer vision problems seeing great progress with strong supervision today. First, we will motivate why this is required for long-term large-scale autonomous robots. Second, we will discuss recent state-of-the-art results obtained in the ML team at Toyota Research Institute (TRI) for unsupervised domain adaptation from simulation and self-supervised depth and pose prediction from monocular imagery. Finally, I will talk about how we actually scale to large datasets using our cloud infrastructure and distributed deep learning.
-- Bio --
Adrien Gaidon is the Manager of the Machine Learning team and a Senior Research Scientist at the Toyota Research Institute (TRI) in Los Altos, CA, USA, working on open problems in world-scale learning for autonomous driving. He received his PhD from Microsoft Research - Inria Paris in 2012 and has over a decade of experience in academic and industrial Computer Vision, with over 30 publications, top entries in international Computer Vision competitions, multiple best reviewer awards, international press coverage for his work on Deep Learning with simulation, and was a guest editor for the International Journal of Computer Vision. You can find him on LinkedIn (https://www.linkedin.com/in/adrien-gaidon-63ab2358/) and Twitter (@adnothing).