Highly reliable vehicle detection through CNN with attention mechanism

Author(s)
Liu, Zhisong
Author(s)
Wang, L.-W.
Yang, X.-F.
Lun, D. P. K.
Date Issued
2022
Publisher
IEEE
Related Publication(s)
Proceedings of 2022 IEEE International Conference on Consumer Electronics (ICCE)
Start page
402
End page
403
Abstract
This paper presents a novel approach to provide reliable vehicle detection by using CNN-based approach and lane information. We firstly propose an adaptive RoI strategy that utilizes road lane information to give focus on frontal area for vehicle detection. Then we introduce a novel attention mechanism that automatically learns an attention map to refine the features for detection. Experimental results show a large improvement (+73 % on recall rate) for long-range (30 to 60m) vehicle detection which is extremely useful for users of driving assistant systems.
URI
DOI
SFU Affiliated Publication
Yes
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