MuVieCAST: Multi-View Consistent Artistic Style Transfer

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Abstract

We introduce MuVieCAST, a modular multi-view consistent style transfer network architecture that enables consistent style transfer between multiple viewpoints of the same scene. This network architecture supports both sparse and dense views, making it versatile enough to handle a wide range of multi-view image datasets. The approach consists of three modules that perform specific tasks related to style transfer, namely content preservation, image transformation, and multi-view consistency enforcement. We extensively evaluate our approach across multiple application domains including depth-map-based point cloud fusion, mesh reconstruction, and novel-view synthesis. Our experiments reveal that the proposed framework achieves an exceptional generation of stylized images, exhibiting consistent outcomes across perspectives. A user study focusing on novel-view synthesis further confirms these results, with approximately 68% of cases participants expressing a preference for our generated outputs compared to the recent state-of-the-art method. Our modular framework is extensible and can easily be integrated with various backbone architectures, making it a flexible solution for multi-view style transfer.
Original languageEnglish
Title of host publicationInternational Conference on 3D Imaging, Modeling, Processing, Visualization and Transmission (3DIMPVT)
PublisherIEEE
Pages1136-1145
Number of pages10
ISBN (Electronic)979-8-3503-6245-9
DOIs
Publication statusPublished - 2024
Event2024 International Conference in 3D Vision - 3DV 2024 - Davos, Switzerland
Duration: 18 Mar 202421 Mar 2024
https://3dvconf.github.io/2024

Publication series

NameProceedings (International Conference on 3D Vision. Online)
PublisherIEEE
ISSN (Electronic)2475-7888

Conference

Conference2024 International Conference in 3D Vision - 3DV 2024
Abbreviated title3DV 2024
Country/TerritorySwitzerland
CityDavos
Period18/03/2421/03/24
Internet address

Bibliographical note

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Keywords

  • point cloud compression
  • geometry
  • image transformation
  • three-dimensional displays
  • focusing
  • estimation
  • network architecture

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