[visionlist] CfP: RSS Workshop on Scene and Situation Understanding for Autonomous Driving (UAD2019)
igilitschenski at mit.edu
Wed May 8 07:14:45 -04 2019
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.
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
* Novel sensing-modalities for improved scene and situation understanding.
* Domain adaptation and transfer learning in the context of autonomous
Submission of Extended Abstracts: May 31, 2019
Notification of Acceptance: June 9, 2019.
Date of the Workshop: June 22, 2019.
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:
=== 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
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