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CVRSUAD 2017 : Fifth Workshop on Computer Vision for Road Scene Understanding and Autonomous Driving

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Link: https://cvrsuad.data61.csiro.au/
 
When Oct 23, 2017 - Oct 23, 2017
Where Venice
Submission Deadline Jul 21, 2017
Notification Due Aug 18, 2017
Final Version Due Aug 25, 2017
Categories    comptuer vision   intelligent vehicles   autonomous driving   robotics
 

Call For Papers

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CALL FOR PAPERS
Fifth Workshop on Computer Vision for Road Scene Understanding and Autonomous Driving
In Conjunction with ICCV 2017, October 23, Venice, Italy
https://cvrsuad.data61.csiro.au/
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Analyzing road scenes using cameras could have a crucial impact in many domains, such as autonomous driving, advanced driver assistance systems (ADAS), personal navigation, mapping of large scale environments and road maintenance. For instance, vehicle infrastructure, signage, and rules of the road have been designed to be interpreted fully by visual inspection. As the field of computer vision becomes increasingly mature, practical solutions to many of these tasks are now within reach. Nonetheless, there still seems to exist a wide gap between what is needed by the automotive industry and what is currently possible using computer vision techniques.

The goal of this workshop is to allow researchers in the fields of road scene understanding and autonomous driving to present their progress and discuss novel ideas that will shape the future of this area. In particular, we would like this workshop to bridge the gap between the community that develops novel theoretical approaches for road scene understanding and the community that builds working real-life systems performing in real-world conditions. To this end, we plan to have a broad panel of invited speakers coming from both academia and industry.

We encourage submissions of original and unpublished work in the area of vision-based road scene understanding. The topics of interest include (but are not limited to):

- Road scene understanding in mature and emerging markets
- Deep learning for road scene understanding
- Prediction and modeling of road scenes and scenarios
- Semantic labeling, object detection and recognition in road scenes
- Dynamic 3D reconstruction, SLAM and ego-motion estimation
- Visual feature extraction, classification and tracking
- Design and development of robust and real-time architectures
- Use of emerging sensors (e.g., multispectral, RGB-D, LIDAR and LADAR)
- Fusion of RGB imagery with other sensing modalities
- Interdisciplinary contributions across computer vision, optics, robotics and other related fields.

We encourage researchers to submit not only theoretical contributions, but also work more focused on applications.

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Important Dates:
Submission Deadline: July 21 (23:59 Pacific Time)
Decisions to authors: August 18
Camera-ready deadline: August 25
Workshop date: October 23
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Submission:
Paper submission is through CMT: https://cmt3.research.microsoft.com/CVRSUAD2017
The format for paper submission is the same as the ICCV 2017 submission format.
Each paper will receive 3 double-blind reviews, which will be moderated by the workshop organizers. More information regarding the submission process can be found at https://cvrsuad.data61.csiro.au.
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Organizers:
Mathieu Salzmann, EPFL, Switzerland
Fredrik Kahl, Chalmers University, Sweden
Jose Alvarez, Data61 - CSIRO, Australia
Bart Nabbe, Aurora Innovation, USA
Lars Petersson, Data61 - CSIRO, Australia

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