Superpixel convolution for segmentation

Teppei Suzuki, Shuichi Akizuki, Naoki Kato, Yoshimitsu Aoki

    研究成果: Conference contribution

    1 被引用数 (Scopus)

    抄録

    In this paper, we propose a novel segmentation algorithm based on convolutional neural networks (CNNs) on superpix-else CNNs are powerful methods for several computer vision tasks, but spatial information disappears through the pooling process. Moreover, since pooling compresses different types of pixels into a single value, pooling sometimes negatively affects the results of inference in segmentation task. We use superpixel pooling instead of general pooling to resolve this problem. However, general CNNs can't use superpixel images in which the adjacency relationships between pixels are broken. Therefore, we define CNNs and Dilated Convolution on superpixels. Finally, we show the effectiveness of proposed method on an HKU-IS dataset.

    本文言語English
    ホスト出版物のタイトル2018 IEEE International Conference on Image Processing, ICIP 2018 - Proceedings
    出版社IEEE Computer Society
    ページ3249-3253
    ページ数5
    ISBN(電子版)9781479970612
    DOI
    出版ステータスPublished - 2018 8 29
    イベント25th IEEE International Conference on Image Processing, ICIP 2018 - Athens, Greece
    継続期間: 2018 10 72018 10 10

    出版物シリーズ

    名前Proceedings - International Conference on Image Processing, ICIP
    ISSN(印刷版)1522-4880

    Conference

    Conference25th IEEE International Conference on Image Processing, ICIP 2018
    CountryGreece
    CityAthens
    Period18/10/718/10/10

    ASJC Scopus subject areas

    • Software
    • Computer Vision and Pattern Recognition
    • Signal Processing

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