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Authors: Jaeseok Choi 1 ; Kyoungmin Lee 2 ; Jisoo Jeong 1 and Nojun Kwak 1

Affiliations: 1 Seoul National University, Seoul and Korea ; 2 SK Holdings, Seoul and Korea

Keyword(s): Object Detection, Computer Vision, Machine Learning, Neural Network, Deep Learning.

Abstract: Recently, a lot of single stage detectors using multi-scale features have been actively proposed. They are much faster than two stage detectors that use region proposal networks (RPN) without much degradation in the detection performances. However, the feature maps in the lower layers close to the input which are responsible for detecting small objects in a single stage detector have a problem of insufficient representation power because they are too shallow. There is also a structural contradiction that the feature maps not only have to deliver low-level information to next layers but also have to contain high-level abstraction for prediction. In this paper, we propose a method to enrich the representation power of feature maps using a new feature fusion method which makes use of the information from the consecutive layer. It also adopts a unified prediction module which has an enhanced generalization performance. The proposed method enables more precise prediction, which achieved h igher or compatible score than other competitors such as SSD and DSSD on PASCAL VOC and MS COCO. In addition, it maintains the advantage of fast computation of a single stage detector, which requires much less computation than other detectors with similar performance. (More)

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Paper citation in several formats:
Choi, J.; Lee, K.; Jeong, J. and Kwak, N. (2019). Two-layer Residual Feature Fusion for Object Detection. In Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods - ICPRAM; ISBN 978-989-758-351-3; ISSN 2184-4313, SciTePress, pages 352-359. DOI: 10.5220/0007306803520359

@conference{icpram19,
author={Jaeseok Choi. and Kyoungmin Lee. and Jisoo Jeong. and Nojun Kwak.},
title={Two-layer Residual Feature Fusion for Object Detection},
booktitle={Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods - ICPRAM},
year={2019},
pages={352-359},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007306803520359},
isbn={978-989-758-351-3},
issn={2184-4313},
}

TY - CONF

JO - Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods - ICPRAM
TI - Two-layer Residual Feature Fusion for Object Detection
SN - 978-989-758-351-3
IS - 2184-4313
AU - Choi, J.
AU - Lee, K.
AU - Jeong, J.
AU - Kwak, N.
PY - 2019
SP - 352
EP - 359
DO - 10.5220/0007306803520359
PB - SciTePress

- Science and Technology Publications, Lda.
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