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Authors: Bing Liu 1 ; Bing Li 2 ; Weiming Hu 2 and Jinfeng Yang 1

Affiliations: 1 Civil Aviation University of China, China ; 2 Chinese Academy of Sciences, China

ISBN: 978-989-758-357-5

Keyword(s): logo detection, Few-example, Three-stage, Model refinement.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Computational Intelligence ; Evolutionary Computing ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Machine Learning ; Soft Computing ; Symbolic Systems

Abstract: Logo detection is a laborious but strong practicality task that has a variety of technology applications. Since the fundamental of state-of-the-art detectors, large-scale annotated datasets, is cost-consuming, few-example logo detection is imperative and thought-provoking. In this paper, a three-stage Few-example Logo Detection Refined System (FLDRS) is proposed to detect logo with a few annotated samples. Specifically, the proposed detector is first initialized using large-scale generic target detection dataset with annotations, such as ImageNet, then further updated with large amount of synthetic logo images, and finally refined with a few annotated real examples. To make synthetic data more closer to real scene, a copy-paste-blend strategy is also presented in our model which not only characterizes many kinds of possible logo transformations but also takes the environment attribute of the logo type into consideration. The superior performance in FlickLogo-32 dataset demonstrates th e efficiency of the proposed FLDRS. (More)

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Paper citation in several formats:
Liu, B.; Li, B.; Hu, W. and Yang, J. (2019). Few-example Logo Detection with Model Refinement.In Proceedings of the International Conference on Advances in Computer Technology, Information Science and Communications - Volume 1: CTISC, ISBN 978-989-758-357-5, pages 122-127. DOI: 10.5220/0008096901220127

@conference{ctisc19,
author={Bing Liu. and Bing Li. and Weiming Hu. and Jinfeng Yang.},
title={Few-example Logo Detection with Model Refinement},
booktitle={Proceedings of the International Conference on Advances in Computer Technology, Information Science and Communications - Volume 1: CTISC,},
year={2019},
pages={122-127},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008096901220127},
isbn={978-989-758-357-5},
}

TY - CONF

JO - Proceedings of the International Conference on Advances in Computer Technology, Information Science and Communications - Volume 1: CTISC,
TI - Few-example Logo Detection with Model Refinement
SN - 978-989-758-357-5
AU - Liu, B.
AU - Li, B.
AU - Hu, W.
AU - Yang, J.
PY - 2019
SP - 122
EP - 127
DO - 10.5220/0008096901220127

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