[visionlist] CfP: RSS Workshop on Scene and Situation Understanding for Autonomous Driving (UAD2019)

[Igor Gilitschenski]

Dear colleagues,

it is our pleasure to invite you to submit extended abstracts for a 
poster at our RSS Workshop on Scene and Situation Understanding for 
Autonomous Driving (UAD2019).

Submission Deadline: May 31, 2019
Workshop Website: https://sites.google.com/view/uad2019

Please find the full CfP below.

Regards,
Igor Gilitschenski on behalf of the organizers



=== Workshop Description ===
Enabling robust, higher-level scene and situation understanding is a key 
challenge to unlock the full potential of autonomous driving. Most 
autonomous driving research has considered the scientific problems 
involved in this challenge as a special instance of either the 
perception or the planning tasks. This workshop takes a scene and 
situation centric approach to discussing advances and future directions 
of autonomous driving research.

Our goal is to bridge the gap between perception, planning, and 
control-based approaches to scene and situation modeling. On the one 
hand, we want to discuss how higher-level scenery information can be 
used to improve the entire autonomy stack, involving localization, 
detection, planning, and control systems. On the other hand, we are 
interested in the interplay of classical perception, planning, and 
control approaches for obtaining an improved scene understanding. In 
that context, we also discuss how recent advances in deep and 
reinforcement learning can be leveraged for impacting basic research and 
actual deployment of autonomous vehicles.


=== Call for Posters ===
Interested researchers from both, academia or industry are invited to 
submit extended abstracts to be presented in spotlight presentations and 
a poster session. The topics of interest involve but are not limited to:
* Situation-aware planning for autonomous vehicles.
* Semantic scene understanding-based approaches to Localization and Mapping.
* Traffic agent trajectory forecasting.
* Intent prediction.
* Multi-Agent reinforcement learning for situation aware planning of 
autonomous vehicles.
* Novel sensing-modalities for improved scene and situation understanding.
* Domain adaptation and transfer learning in the context of autonomous 
driving.

Important Dates:
Submission of Extended Abstracts: May 31, 2019
Notification of Acceptance: June 9, 2019.
Date of the Workshop: June 22, 2019.

Submission Information:
Extended abstracts of the posters can be submitted as PDF file in RSS 
format (2-6 pages, no double blind submission required, file size should 
not exceed 10MB). Accepted posters will be presented in the workshop. 
The pdf of the posters alongside with the extended abstracts will be 
published on the workshop website. More information can be found at:

https://sites.google.com/view/uad2019/submission


=== Invited Speakers ===
We are proud to have a group of diverse invited speakers covering the 
entire spectrum of scene and and situation understanding research:
* Wolfram Burgard, Toyota Research Institute & University of Freiburg
* Darius Burschka, TU Munich
* Andrea Censi, ETH Zurich & Aptiv Autonomous Mobility
* Alexey Dosovitskiy, Google
* Yohannes Kassahun, Audi
* Daniela Rus, MIT
* Elena Stumm, Zoox
* Fisher Yu, UC Berkeley


=== Organizers ===
Igor Gilitschenski, MIT
Juan Nieto, ETH Zürich
Federico Tombari, TUM & Google
Daniela Rus, MIT

-- 
Igor Gilitschenski, Senior Postdoctoral Associate
MIT - Computer Science and Artificial Intelligence Laboratory
32 Vassar Street | Room 32-379 | Cambridge, MA 02139