Document Type
Article
Publication Title
Arts & Communication
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.
Publication Date
11-2023
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Recommended Citation
O'Brien, Charles; Hutson, James; Olsen, Trent; and Ratican, Jay, "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" (2023). Faculty Scholarship. 522.
https://digitalcommons.lindenwood.edu/faculty-research-papers/522