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A Small Scale Multi-Column Network for Aesthetic Classification Based on Multiple Attributes

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Neural Information Processing (ICONIP 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10634))

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Abstract

Image aesthetic quality assessment, which devotes to distinguishing whether an image is beautiful or not, has drawn a lot of attention in recent years. Recently deep learning has shown great power in data analysis and has been widely used in this field. However, on the one hand, deep learning is an end-to-end learning method that can be easily influenced by noisy data. On the other hand, prior information concluded from the experience of human perception of aesthetics, which widely applied in traditional aesthetic assessment methods, has not been effectively utilized in deep learning based aesthetic quality assessment methods. Therefore, in this paper we embed these prior information in deep learning as guidance for aesthetic quality assessment. Firstly, we design an extremely small network with only 38 K parameters for better training. Then we propose a multi-column network architecture to embed prior information into our deep learning model. We train our proposed network on AVA dataset, which is widely used for aesthetic assessment. The experimental results show that prior information indeed guides our network to learn better.

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Acknowledgments

This work is supported by the 973 project 2015CB351803, NSFC No. 61572451 and No. 61390514, Youth Innovation Promotion Association CAS CX2100060016, and Fok Ying Tung Education Foundation WF2100060004.

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Authors and Affiliations

  1. CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System, University of Science and Technology of China, Anhui, 230027, China

    Chaoqun Wan & Xinmei Tian

Authors
  1. Chaoqun Wan
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  2. Xinmei Tian
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Corresponding author

Correspondence to Xinmei Tian .

Editor information

Editors and Affiliations

  1. Guangdong University of Technology, Guangzhou, China

    Derong Liu

  2. Guangdong University of Technology, Guangzhou, China

    Shengli Xie

  3. South China University of Technology, Guangzhou, China

    Yuanqing Li

  4. Institute of Automation, Chinese Academy of Sciences, Beijing, China

    Dongbin Zhao

  5. King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia

    El-Sayed M. El-Alfy

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Wan, C., Tian, X. (2017). A Small Scale Multi-Column Network for Aesthetic Classification Based on Multiple Attributes. In: Liu, D., Xie, S., Li, Y., Zhao, D., El-Alfy, ES. (eds) Neural Information Processing. ICONIP 2017. Lecture Notes in Computer Science(), vol 10634. Springer, Cham. https://doi.org/10.1007/978-3-319-70087-8_94

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  • DOI: https://doi.org/10.1007/978-3-319-70087-8_94

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-70086-1

  • Online ISBN: 978-3-319-70087-8

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