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Radar as a teacher: weakly supervised vehicle detection using radar labels

Abstract:

It has been demonstrated that the performance of an object detector degrades when it is used outside the domain of the data used to train it. However, obtaining training data for a new domain can be time consuming and expensive. In this work we demonstrate how a radar can be used to generate plentiful (but noisy) training data for image-based vehicle detection. We then show that the performance of a detector trained using the noisy labels can be considerably improved through a combination of ...

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Publication status:
Published
Peer review status:
Reviewed (other)

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Publisher copy:
10.1109/ICRA40945.2020.9196855

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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
ORCID:
0000-0001-6562-8454
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Name:
Engineering & Physical Sciences Research Council
Grant:
EP/M019918/1
Publisher:
IEEE
Journal:
Proceedings of the 2020 IEEE International Conference on Robotics and Automation (ICRA) More from this journal
Pages:
222-228
Publication date:
2020-09-15
Acceptance date:
2019-12-23
Event title:
International Conference on Robotics and Automation 2020
Event location:
Online
Event website:
https://www.icra2020.org/
Event start date:
2020-05-31
Event end date:
2020-08-31
DOI:
EISSN:
2577-087X
ISSN:
1050-4729
EISBN:
978-1-7281-7395-5
ISBN:
978-1-7281-7396-2
Language:
English
Keywords:
Pubs id:
1113000
Local pid:
pubs:1113000
Deposit date:
2020-06-18

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