IADIS International Journal on Computer Science and Information Systems

Published by IADIS (International Association for Development of the Information Society) • ISSN (Online): 1646-3692 • ISSN (Print): 1646-3692
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Sp3f-gan: Generating Seamless Texture Maps for Fashion

Honghong He *
Zhengwentai Sun *
Jintu Fan *
Pik Yin Mok *
* 1School of Fashion and Textiles, The Hong Kong Polytechnic University, Hong Kong 2Labortary for Artificial Intelligence in Design, Hong Kong Science Park, Hong Kong (Portugal)
* 1School of Fashion and Textiles, The Hong Kong Polytechnic University, Hong Kong 2Labortary for Artificial Intelligence in Design, Hong Kong Science Park, Hong Kong (Portugal)
* 1School of Fashion and Textiles, The Hong Kong Polytechnic University, Hong Kong 2Labortary for Artificial Intelligence in Design, Hong Kong Science Park, Hong Kong (Portugal)
* 1School of Fashion and Textiles, The Hong Kong Polytechnic University, Hong Kong 2Labortary for Artificial Intelligence in Design, Hong Kong Science Park, Hong Kong (Portugal)

Abstract

Creating seamless textures is crucial to attain realistic 3D virtual objects and environments. This is because when stochastic textures are tiled in a straightforward manner, they produce cluttered visuals with noticeable seams that lack authenticity. This paper proposes GAN -based method for automatic seamless texture synthesis by designing th ree main components in generator block: (i) the texture style encoder, (ii) residual tiling blocks and (iii) the BRDFs tileable decoder in the generator of an adversarial expansion network, resulting in a continuous texture output at the seam intersection area. In addition, considering the different properties of virtual environment rendering materials, the spatially varying BRDFs (albedo, normal, roughness and displacement map) are all designed in the proposed model to handle multi -layer texture representation. Furthermore, the proposed method for generating seamless multi-layer texture maps that incorporates different loss functions, allowing us to control both the geometric shape and visual fidelity of the synthesized textures. Qualitative and quantitati ve experiments on the describable textures dataset (DTD) show that the generated texture maps are not only seamlessly tiled but also exhibit superior visual quality in preserving details compared to previous deep texture synthesis methods.

Keywords

Generative Adversarial Network (GAN) Seamless texture synthesis BRDFs Image generation Fashion
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Funding: This research received academic dissemination support through ESCAP / JournalsHub publishing programs.
Conflicts of Interest: The authors declare no competing financial or institutional interests.
Peer Review: Double-blind peer reviewed by international subject specialists.
License: Creative Commons Attribution 4.0 International (CC BY 4.0).
How to Cite This Article
APA / MLA / BibTeX
He, et al. (2023). Sp3f-gan: Generating Seamless Texture Maps for Fashion. IADIS International Journal on Computer Science and Information Systems, 18(2). https://doi.org/10.33965/ijcsis_2023_v18i2_11
He, et al. "Sp3f-gan: Generating Seamless Texture Maps for Fashion." IADIS International Journal on Computer Science and Information Systems, vol. 18, no. 2, 2023. https://doi.org/10.33965/ijcsis_2023_v18i2_11
He, et al. "Sp3f-gan: Generating Seamless Texture Maps for Fashion." IADIS International Journal on Computer Science and Information Systems 18, no. 2 (2023). https://doi.org/10.33965/ijcsis_2023_v18i2_11