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Research Article | Open Access

User-oriented interactive style transfer

BNRist, Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China
College of Computer Science, Nankai University, Tianjin, China
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Abstract

Neural style transfer (NST) can create impressive artworks by transferring a reference style to a content image. Current image-to-image NST methods lack the fine-grained control often demanded for artistic editing. To mitigate this limitation, we propose a user-oriented interactive style transfer (IST) method, using which a harmonious image like drawing can be interactively created. Our IST method can serve as a brush, dipping style from anywhere, and then painting to any region of the target content image. To control the action scope, we formulate a fluid simulation algorithm, which takes styles as pigments around the position of brush interaction, and uses diffusion in style or content images according to similarity maps. By dipping and painting, even employing a single style image can produce thousands of eye-catching works. Our method expands the creative capabilities of NST.

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Computational Visual Media
Pages 1441-1457

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Cite this article:
Lin Z, Zhang Z, Zhang K-R, et al. User-oriented interactive style transfer. Computational Visual Media, 2026, 12(5): 1441-1457. https://doi.org/10.26599/CVM.2026.9450481

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Received: 29 July 2024
Accepted: 22 February 2025
Published: 14 October 2026
© The Author(s) 2026.

This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made.

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