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Principal Semantic Feature Analysis with Covariance Attention

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Pattern Recognition and Computer Vision (PRCV 2020)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 12306))

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Abstract

In this work, we present a new module for semantic segmentation. This new module is designed as a plug in module for the backbone networks to further boosting the segmentation performance using the principal semantic feature analysis with covariance attention. Specifically, the spatial and channel covariance attention module are designed respectively, which can filter noisy regions and help the CNN to adaptively extract the dominant semantic content. By using the proposed covariance attention modules, a covariance attention architecture is built over FCN. Experimental results demonstrate the substantial benefits brought by the proposed covariance attention scheme, and show that the covariance attention mechanism is feasible and effective for improving the accuracy of semantic segmentation.

Y. Chen—Student as the first author.

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Author information

Authors and Affiliations

  1. The School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, 210094, China

    Yuliang Chen, Yazhou Liu & Quansen Sun

  2. The Panasonic R&D Center Singapore, Singapore, 469332, Singapore

    Pongsak Lasang

Authors
  1. Yuliang Chen
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  2. Yazhou Liu
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  3. Pongsak Lasang
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  4. Quansen Sun
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Corresponding author

Correspondence to Yazhou Liu .

Editor information

Editors and Affiliations

  1. Peking University, Beijing, China

    Yuxin Peng

  2. Nanjing University of Information Science and Technology, Nanjing, China

    Qingshan Liu

  3. Dalian University of Technology, Dalian, China

    Huchuan Lu

  4. Chinese Academy of Sciences, Beijing, China

    Zhenan Sun

  5. Chinese Academy of Sciences, Beijing, China

    Chenglin Liu

  6. Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China

    Xilin Chen

  7. Peking University, Beijing, China

    Hongbin Zha

  8. Nanjing University of Science and Technology, Nanjing, China

    Jian Yang

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Chen, Y., Liu, Y., Lasang, P., Sun, Q. (2020). Principal Semantic Feature Analysis with Covariance Attention. In: Peng, Y., et al. Pattern Recognition and Computer Vision. PRCV 2020. Lecture Notes in Computer Science(), vol 12306. Springer, Cham. https://doi.org/10.1007/978-3-030-60639-8_19

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  • DOI: https://doi.org/10.1007/978-3-030-60639-8_19

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-60638-1

  • Online ISBN: 978-3-030-60639-8

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