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Limitations and possibilities of digital restoration techniques using generative AI tools: Reconstituting Antoine François Callet’s Achilles Dragging Hector’s Body Past the Walls of Troy
Charles O’Brien1 ,
James Hutson2* ,
Trent Olsen2 ,
Jeremiah Ratican3
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1
Department of Art, Art History, and Design, University of Alabama in Huntsville, Huntsville, Alabama,
USA
2
Department of Art History and Visual Culture, College of Arts and Humanities, Lindenwood University, Saint Charles, Missouri,
USA
3
Department of Art, Media, and Production, College of Arts and Humanities, Lindenwood University, Saint Charles, Missouri,
USA
Submitted: 11 September 2023 | Accepted: 1 November 2023 | Published: 8 November 2023
© 2023 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution -Noncommercial 4.0 International License (CC-by the license) ( https://creativecommons.org/licenses/by-nc/4.0/ )
Abstract
Digital restoration offers new avenues for conserving historical artworks, yet presents unique challenges. This research delves into the balance between traditional restoration methods and the use of generative artificial intelligence (AI) tools, using Antoine François Callet’s portrayal of Achilles Dragging Hector’s Body Past the Walls of Troy as a case study. The application of Easy Diffusion and Stable Diffusion 2.1 technologies provides insights into AI-driven restoration methods such as inpainting and colorization. Results indicate that while AI can streamline the restoration process, repeated inpainting can compromise the painting’s color quality and detailed features. Furthermore, the AI approach occasionally introduces unintended visual discrepancies, especially with repeated application. With evolving restoration tools, adaptability remains crucial. Integrating both AI and traditional techniques seems promising, though it is essential to maintain the artwork’s inherent authenticity. This study offers valuable perspectives for art historians, conservators, and AI developers, enriching discussions about the potential and pitfalls of AI in art restoration.
Keywords
Digital restoration
Generative artificial intelligence
Stable diffusion
Inpainting techniques
Synergistic techniques
Art restoration
Funding
None.
Conflict of interest
The authors declare that they have no conflicts of interest.
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