Prof. Dr. Daniel Cremers

Chair for Computer Vision & Pattern Recognition Technical University of Munich
Prof. Dr. Daniel Cremers obtained a PhD in Computer Science from the University of Mannheim, Germany. Subsequently he spent two years as a postdoctoral researcher at the University of California at Los Angeles (UCLA) and one year as a permanent researcher at Siemens Corporate Research in Princeton, NJ. From 2005 until 2009 he was associate professor at the University of Bonn, Germany. Since 2009 he holds the chair for Computer Vision and Pattern Recognition at the Technical University, Munich. He coauthored more than 300 publications which received numerous awards. In December 2010 he was listed among "Germany's top 40 researchers below 40" (Capital). Prof. Cremers received the Gottfried-Wilhelm Leibniz Award 2016, the most important research award in German academia.

Agenda Day 1

Tuesday, October 22nd, 2019

9:00 AM Opening remarks

1:50 PM Panel discussion | What are strengths and weaknesses of deep neural networks?

Selected experts of the day from both industries will join the panel to discuss their vision and
experiences, and come to the best solution in the following topics:
• What is the current role of AI in a vehicle?
• What are advantages of using deep neural networks in the vehicle and what are their best
applications?
• What are the pitfalls of current neural network technology and how can it be improved?

2:30 PM New algorithms for camera-based real-time localization and mapping

This talk glimpses into recent developments of computer vision algorithms for simultaneous
localization and mapping (SLAM). In particular, it introduces direct methods for visual SLAM. In
contrast to classical key point-based methods they directly exploit all available brightness
information. As a consequence, they provide drastic improvements in precision and robustness.
Furthermore, it will be demonstrated how one can further boost precision and robustness by fusion
visual information with inertial and GPS information. Ultimately this leads to a system for realtime
localization and mapping with unprecedented precision and robustness that can be deployed in a
multitude of autonomous systems ranging from robots and drones to self-driving cars.

5:40 PM Closing remarks

Check out the incredible speaker line-up to see who will be joining Daniel.

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