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StyleDisentangle: Disentangled Image Editing Based on StyleGAN2

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PRICAI 2023: Trends in Artificial Intelligence (PRICAI 2023)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 14325))

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Abstract

Thanks to the development of Generative Adversarial Networks (GANs), StyleGAN2 can generate highly realistic images by inputting a latent code and then editing them in the latent space. Disentangled image editing is crucial, where the goal is to change the desired attributes of an image while keeping the other attributes intact. As a solution, we introduce the StyleDisentangle framework for image editing. The fundamental concept of StyleDisentangle is to define attributes through two distinct sets of information: semantic segmentation coordinates - identifying the region in the image related to the attribute, and latent code coordinates - identifying the dimensions related to attributes in latent code. By utilizing these two distinct sets of coordinates, we can precisely determine the position of each attribute within the attribute editing space, resulting in disentangled image editing. We conducted extensive experiments to demonstrate the effectiveness of our method on multiple datasets and additionally compared our results with state-of-the-art methods.

Supported by Tianjin Technical Export Project 20YDTPJC01570.

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Authors and Affiliations

  1. College of Intelligence and Computing, Tianjin University, Tianjin, 300350, China

    Xuewei Li, Xuzhou Fu, Jie Gao & Zhiqiang Liu

  2. Tianjin Key Laboratory of Cognitive Computing and Application, Tianjin, 300350, China

    Xuewei Li, Xuzhou Fu, Jie Gao & Zhiqiang Liu

  3. Tianjin Key Laboratory of Advanced Networking, Tianjin, 300350, China

    Xuewei Li, Xuzhou Fu, Jie Gao & Zhiqiang Liu

  4. Tianjin International Engineering Institute, Tianjin University, Tianjin, 300350, China

    Xuewei Li & Siyuan Ping

Authors
  1. Xuewei Li
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  2. Siyuan Ping
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  3. Xuzhou Fu
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  4. Jie Gao
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  5. Zhiqiang Liu
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Corresponding author

Correspondence to Zhiqiang Liu .

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Editors and Affiliations

  1. Tsinghua University, Beijing, China

    Fenrong Liu

  2. SEEK Limited, Cremorne, NSW, Australia

    Arun Anand Sadanandan

  3. MIMOS (Malaysia), Kuala Lumpur, Malaysia

    Duc Nghia Pham

  4. Universitas Indonesia, Depok, Indonesia

    Petrus Mursanto

  5. Tabcorp Holdings Limited, Melbourne, VIC, Australia

    Dickson Lukose

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© 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Li, X., Ping, S., Fu, X., Gao, J., Liu, Z. (2024). StyleDisentangle: Disentangled Image Editing Based on StyleGAN2. In: Liu, F., Sadanandan, A.A., Pham, D.N., Mursanto, P., Lukose, D. (eds) PRICAI 2023: Trends in Artificial Intelligence. PRICAI 2023. Lecture Notes in Computer Science(), vol 14325. Springer, Singapore. https://doi.org/10.1007/978-981-99-7019-3_27

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  • DOI: https://doi.org/10.1007/978-981-99-7019-3_27

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-7018-6

  • Online ISBN: 978-981-99-7019-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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