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A Survey on 3D Style Transfer

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Tools for Design, Implementation and Verification of Emerging Information Technologies (TridentCom 2022)

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Abstract

Image style transfer is a popular and widely studied task in computer vision, and it aims to apply the style of the source image to the target while the target remains its original content. Style transfer is widely used in creating new images in 2D, but style transfer in 3D images still has many challenges. In this paper, we summarize the major existing methods of 3D style transfer, including traditional and neural network based approaches. Moreover, we discuss the application field and the future research direction in 3D style transfer.

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Acknowledgment

This work was supported partly by the 2021 National pre-research project of Suzhou City University (2021SGY010).

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Authors and Affiliations

  1. Suzhou City University, Suzhou, China

    Qifeng Zhu, Min Sun & Jiang Wang

Authors
  1. Qifeng Zhu
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  2. Min Sun
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  3. Jiang Wang
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Corresponding author

Correspondence to Qifeng Zhu .

Editor information

Editors and Affiliations

  1. University of Technology Sydney, Sydney, NSW, Australia

    Shui Yu

  2. National Supercomputer Center, Jinan, China

    Bruce Gu

  3. CSIRO Data61, Sydney, NSW, Australia

    Youyang Qu

  4. Melbourne Polytechnic, Melbourne, VIC, Australia

    Xiaodong Wang

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Zhu, Q., Sun, M., Wang, J. (2023). A Survey on 3D Style Transfer. In: Yu, S., Gu, B., Qu, Y., Wang, X. (eds) Tools for Design, Implementation and Verification of Emerging Information Technologies. TridentCom 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 489. Springer, Cham. https://doi.org/10.1007/978-3-031-33458-0_10

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  • DOI: https://doi.org/10.1007/978-3-031-33458-0_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-33457-3

  • Online ISBN: 978-3-031-33458-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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