Unsupervised Colorization and Diffusion-Based Virtual Try-On for Ottoman Heritage Preservation
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Date
2025
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
Colorizing historical images and modernizing traditional attire are key to bridging past and present in digital heritage preservation. Accurate colorization improves the interpretation of old photos, while modernizing historical attire supports cultural adaptation and fashion preservation. This paper presents an unsupervised method for colorizing 19th century images using GANs, trained with a dataset from modern-historical films. By leveraging the GAN discriminator, realistic colorizations are generated without paired data, capturing the textures and authenticity of historical scenes. A diverse film-based dataset enables the model to generalize across eras. Additionally, historical clothing is segmented and transferred onto modern subjects using diffusion-based virtual try-on techniques. Together, these methods support cultural preservation by blending historical accuracy with modern representation.
Description
CCS Concepts: Computing methodologies → Image colorization; Computer vision tasks; Generative adversarial networks
@inproceedings{10.2312:dh.20253174,
booktitle = {Digital Heritage},
editor = {Campana, Stefano and Ferdani, Daniele and Graf, Holger and Guidi, Gabriele and Hegarty, Zackary and Pescarin, Sofia and Remondino, Fabio},
title = {{Unsupervised Colorization and Diffusion-Based Virtual Try-On for Ottoman Heritage Preservation}},
author = {Akant, Zeynep and Ghazaei, Elman and Balcisoy, Selim},
year = {2025},
publisher = {The Eurographics Association},
ISBN = {978-3-03868-277-6},
DOI = {10.2312/dh.20253174}
}