Unsupervised Colorization and Diffusion-Based Virtual Try-On for Ottoman Heritage Preservation

Simple item page
dc.contributor.authorAkant, Zeynepen_US
dc.contributor.authorGhazaei, Elmanen_US
dc.contributor.authorBalcisoy, Selimen_US
dc.contributor.editorCampana, Stefanoen_US
dc.contributor.editorFerdani, Danieleen_US
dc.contributor.editorGraf, Holgeren_US
dc.contributor.editorGuidi, Gabrieleen_US
dc.contributor.editorHegarty, Zackaryen_US
dc.contributor.editorPescarin, Sofiaen_US
dc.contributor.editorRemondino, Fabioen_US
dc.date.accessioned2025-09-05T20:06:13Z
dc.date.available2025-09-05T20:06:13Z
dc.date.issued2025
dc.description.abstractColorizing 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.en_US
dc.description.sectionheadersDigitization Tools and Applications
dc.description.seriesinformationDigital Heritage
dc.identifier.doi10.2312/dh.20253174
dc.identifier.isbn978-3-03868-277-6
dc.identifier.pages5 pages
dc.identifier.urihttps://doi.org/10.2312/dh.20253174
dc.identifier.urihttps://diglib.eg.org/handle/10.2312/dh20253174
dc.publisherThe Eurographics Associationen_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectCCS Concepts: Computing methodologies → Image colorization; Computer vision tasks; Generative adversarial networks
dc.subjectComputing methodologies → Image colorization
dc.subjectComputer vision tasks
dc.subjectGenerative adversarial networks
dc.titleUnsupervised Colorization and Diffusion-Based Virtual Try-On for Ottoman Heritage Preservationen_US
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
dh20253174.pdf
Size:
787.66 KB
Format:
Adobe Portable Document Format
Download
Collections
Track 04 – Acquisition and Digitization