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Sequential Deformation for Accurate Scene Text Detection

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Computer Vision – ECCV 2020 (ECCV 2020)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 12374))

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Abstract

Scene text detection has been significantly advanced over recent years, especially after the emergence of deep neural network. However, due to high diversity of scene texts in scale, orientation, shape and aspect ratio, as well as the inherent limitation of convolutional neural network for geometric transformations, to achieve accurate scene text detection is still an open problem. In this paper, we propose a novel sequential deformation method to effectively model the line-shape of scene text. An auxiliary character counting supervision is further introduced to guide the sequential offset prediction. The whole network can be easily optimized through an end-to-end multi-task manner. Extensive experiments are conducted on public scene text detection datasets including ICDAR 2017 MLT, ICDAR 2015, Total-text and SCUT-CTW1500. The experimental results demonstrate that the proposed method has outperformed previous state-of-the-art methods.

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Acknowledgement

The authors would like to thank the reviewers for their valuable comments to improve the quality of the paper. This research is supported by a joint research project between Hyundai Motor Group AIRS Company and Tsinghua University. The second author is partially supported by National Key R&D Program of China and a grant from the Institute for Guo Qiang, Tsinghua University.

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Authors and Affiliations

  1. Department of Electronic Engineering, Beijing National Research Center for Information Science and Technology, Tsinghua University, Beijing, China

    Shanyu Xiao, Liangrui Peng, Ruijie Yan, Keyu An & Gang Yao

  2. Hyundai Motor Group AIRS Company, Seoul, Korea

    Jaesik Min

Authors
  1. Shanyu Xiao
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  2. Liangrui Peng
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  3. Ruijie Yan
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  4. Keyu An
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  5. Gang Yao
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  6. Jaesik Min
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Corresponding author

Correspondence to Liangrui Peng .

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Editors and Affiliations

  1. University of Oxford, Oxford, UK

    Andrea Vedaldi

  2. Graz University of Technology, Graz, Austria

    Horst Bischof

  3. University of Freiburg, Freiburg im Breisgau, Germany

    Thomas Brox

  4. University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

    Jan-Michael Frahm

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Xiao, S., Peng, L., Yan, R., An, K., Yao, G., Min, J. (2020). Sequential Deformation for Accurate Scene Text Detection. In: Vedaldi, A., Bischof, H., Brox, T., Frahm, JM. (eds) Computer Vision – ECCV 2020. ECCV 2020. Lecture Notes in Computer Science(), vol 12374. Springer, Cham. https://doi.org/10.1007/978-3-030-58526-6_7

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  • DOI: https://doi.org/10.1007/978-3-030-58526-6_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-58525-9

  • Online ISBN: 978-3-030-58526-6

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