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Synchronized Multi-Frame Diffusion for Temporally Consistent Video Stylization

  • Minshan Xie
  • , Hanyuan Liu
  • , Chengze Li
  • , Tien-Tsin Wong

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

37 Downloads (CityUHK Scholars)

Abstract

Text-guided video-to-video stylization transforms the visual appearance of a source video to a different appearance guided on textual prompts. Existing text-guided image diffusion models can be extended for stylized video synthesis. However, they struggle to generate videos with both highly detailed appearance and temporal consistency. In this paper, we propose a synchronized multi-frame diffusion framework to maintain both the visual details and the temporal consistency. Frames are denoised in a synchronous fashion, and more importantly, information of different frames is shared since the beginning of the denoising process. Such information sharing ensures that a consensus, in terms of the overall structure and color distribution, among frames can be reached in the early stage of the denoising process before it is too late. The optical flow from the original video serves as the connection, and hence the venue for information sharing, among frames. We demonstrate the effectiveness of our method in generating high-quality and diverse results in extensive experiments. Our method shows superior qualitative and quantitative results compared to state-of-the-art video editing methods. © 2025 The Author(s). Computer Graphics Forum published by Eurographics - The European Association for Computer Graphics and John Wiley & Sons Ltd.
Original languageEnglish
Article numbere70095
Number of pages12
JournalComputer Graphics Forum
Volume44
Issue number2
Online published16 Apr 2025
DOIs
Publication statusPublished - May 2025

Funding

Open access publishing facilitated by Monash University as part of the Wiley-Monash University agreement via the Council of Australian University Librarians. This work was also supported by the Research Grants Council of the Hong Kong SAR, China (Project No. UGC/FDS11/E02/23).

Research Keywords

  • CCS Concepts
  • Image processing
  • • Computing methodologies → Computer vision tasks

Publisher's Copyright Statement

  • This full text is made available under CC-BY 4.0. https://creativecommons.org/licenses/by/4.0/

RGC Funding Information

  • RGC-funded

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