Face image generation system using attribute information with DCGANs

Yurika Sagawa, Masafumi Hagiwara

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we propose an attribute added face image generation system using Deep Convolutional Generative Adversarial Networks(DCGANs). Convolutional Neural Networks(CNNs) can extract important features of an image and attain high precision in image classification tasks. In the proposed system, image features are extracted using CNNs, and attribute features added to image features, and attributes added images are generated by DCGANs. Specifically, we use the attributes of "smile" and "male", and work on a task of generating smile images from non-smile images, and a task of generating male images from female images. Since the training of the proposed system requires image pairs including with and without attributes, we use two extraction methods, 1)Usage of attribute label attached dataset, 2)Usage of cosine similarity. To obtain attribute features, we trained 4-layer CNNs which are the same architecture as Discriminator of GANs, to classify images into two classes, with and without attributes. Here, attribute features are defined as the averaged difference between image features with and without attributes, more specifically, the values in the final convolution layer in the 4-layer CNNs. We performed two kinds of evaluation experiments: the first one is a subjective evaluation experiment on items such as "whether generated images have attributes", the second one is a quantitative evaluation experiment for measuring whether the people shown in the input image and the generated image are the same person. As the results, excellent characteristics were obtained.

Original languageEnglish
Title of host publication2nd International Conference on Machine Learning and Soft Computing, ICMLSC 2018
PublisherAssociation for Computing Machinery
Pages109-113
Number of pages5
ISBN (Electronic)9781450363365
DOIs
Publication statusPublished - 2018 Feb 2
Event2nd International Conference on Machine Learning and Soft Computing, ICMLSC 2018 - Phu Quoc Island, Viet Nam
Duration: 2018 Feb 22018 Feb 4

Other

Other2nd International Conference on Machine Learning and Soft Computing, ICMLSC 2018
CountryViet Nam
CityPhu Quoc Island
Period18/2/218/2/4

Keywords

  • Convolutional neural networks
  • Deep convolutional generative adversarial networks
  • Image generation

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Software

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  • Cite this

    Sagawa, Y., & Hagiwara, M. (2018). Face image generation system using attribute information with DCGANs. In 2nd International Conference on Machine Learning and Soft Computing, ICMLSC 2018 (pp. 109-113). Association for Computing Machinery. https://doi.org/10.1145/3184066.3184071