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FSSSD: Fixed scale SSD for vehicle detection

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Author(s)
Jun J.Pak H.Jeon M.
Type
Conference Paper
Citation
15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2020, pp.336 - 342
Issued Date
2020-02-27
Abstract
Since surveillance cameras are commonly installed in high places, the objects in the taken images are relatively small. Detecting small objects is a hard issue for the one-stage detector, and its performance in the surveillance system is not good. Two-stage detectors work better, but their speed is too slow to use in the real-time system. To remedy the drawbacks, we propose an efficient method, named as Fixed Scale SSD(FSSSD), which is an extension of SSD. The proposed method has three key points: high-resolution inputs to detect small objects, a lightweight Backbone to speed up, and prediction blocks to enrich features. FSSSD achieve 63.7% AP at 16.7 FPS in the UA-DETRAC test dataset. The performance is similar to two-stage detectors and faster than any other one-stage method. Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved
Publisher
SciTePress
Conference Place
EI
URI
https://scholar.gist.ac.kr/handle/local/22786
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