Staff View: Use of AI to Recreate and Repatriate Lost, Destroyed or Stolen Paintings: The 1785 Parisian Salon Case Study

Use of AI to Recreate and Repatriate Lost, Destroyed or Stolen Paintings: The 1785 Parisian Salon Case Study

This study investigates the efficacy of artificial intelligence (AI) in the field of artwork restoration, focusing on lost, stolen, or destroyed artworks. Employing a dual approach that combines traditional manual restoration techniques with advanced generative AI tools, the research centers on a...

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Main Authors:	O'Brien, C., Hutson, J., Olsen, T., Ratican, J.
Format:	Article
Language:	English
Published:	INTI International University 2023
Subjects:	NC Drawing Design Illustration QA76 Computer software T Technology (General)
Online Access:	http://eprints.intimal.edu.my/1883/1/joit2023_21.pdf http://eprints.intimal.edu.my/1883/ http://ipublishing.intimal.edu.my/joint.html
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id	my-inti-eprints.1883
record_format	eprints
spelling	my-inti-eprints.18832024-01-31T02:07:23Z http://eprints.intimal.edu.my/1883/ Use of AI to Recreate and Repatriate Lost, Destroyed or Stolen Paintings: The 1785 Parisian Salon Case Study O'Brien, C. Hutson, J. Olsen, T. Ratican, J. NC Drawing Design Illustration QA76 Computer software T Technology (General) This study investigates the efficacy of artificial intelligence (AI) in the field of artwork restoration, focusing on lost, stolen, or destroyed artworks. Employing a dual approach that combines traditional manual restoration techniques with advanced generative AI tools, the research centers on a case study of the 1785 Parisian Salon. Itspecifically examines the reconstitution of Antoine François Callet's painting, Achilles Dragging the Body of Hector, unveiled alongside Jacques-Louis David's Oath of the Horatii. The study utilizes Easy Diffusion and Stable Diffusion 2.1 technologies for inpainting and colorization processes. These AI tools are employed in concert with manual restoration practices to recreate the Callet painting. The methodology also includes the use of secondary visual materials, such as Pietro Martini's 1785 engraving of the Salon Carré, to inform the AI's trained dataset. The application of generative AI in this context significantly accelerates the restoration process. However, the study identifies a critical issue where successive AI-based inpainting iterations lead to a degradation in color fidelity and detail precision. This degradation is evidenced by the emergence of unintended artifacts and a loss of visual coherence in the restored images. While AI significantly expedites the artwork restoration process, its integration with manual techniques is crucial to mitigate the loss of artistic detail and color accuracy. The study's findings emphasize the need for a balanced approach that leverages the strengths of both AI and traditional restoration methods. This integrative strategy is essential for preserving the original artistic essence of artworks, contributing significantly to the fields of art restoration and digital humanities. INTI International University 2023-12 Article PeerReviewed text en cc_by_4 http://eprints.intimal.edu.my/1883/1/joit2023_21.pdf O'Brien, C. and Hutson, J. and Olsen, T. and Ratican, J. (2023) Use of AI to Recreate and Repatriate Lost, Destroyed or Stolen Paintings: The 1785 Parisian Salon Case Study. Journal of Innovation and Technology, 2023 (21). pp. 1-12. ISSN 2805-5179 http://ipublishing.intimal.edu.my/joint.html
institution	INTI International University
building	INTI Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	INTI International University
content_source	INTI Institutional Repository
url_provider	http://eprints.intimal.edu.my
language	English
topic	NC Drawing Design Illustration QA76 Computer software T Technology (General)
spellingShingle	NC Drawing Design Illustration QA76 Computer software T Technology (General) O'Brien, C. Hutson, J. Olsen, T. Ratican, J. Use of AI to Recreate and Repatriate Lost, Destroyed or Stolen Paintings: The 1785 Parisian Salon Case Study
description	This study investigates the efficacy of artificial intelligence (AI) in the field of artwork restoration, focusing on lost, stolen, or destroyed artworks. Employing a dual approach that combines traditional manual restoration techniques with advanced generative AI tools, the research centers on a case study of the 1785 Parisian Salon. Itspecifically examines the reconstitution of Antoine François Callet's painting, Achilles Dragging the Body of Hector, unveiled alongside Jacques-Louis David's Oath of the Horatii. The study utilizes Easy Diffusion and Stable Diffusion 2.1 technologies for inpainting and colorization processes. These AI tools are employed in concert with manual restoration practices to recreate the Callet painting. The methodology also includes the use of secondary visual materials, such as Pietro Martini's 1785 engraving of the Salon Carré, to inform the AI's trained dataset. The application of generative AI in this context significantly accelerates the restoration process. However, the study identifies a critical issue where successive AI-based inpainting iterations lead to a degradation in color fidelity and detail precision. This degradation is evidenced by the emergence of unintended artifacts and a loss of visual coherence in the restored images. While AI significantly expedites the artwork restoration process, its integration with manual techniques is crucial to mitigate the loss of artistic detail and color accuracy. The study's findings emphasize the need for a balanced approach that leverages the strengths of both AI and traditional restoration methods. This integrative strategy is essential for preserving the original artistic essence of artworks, contributing significantly to the fields of art restoration and digital humanities.
format	Article
author	O'Brien, C. Hutson, J. Olsen, T. Ratican, J.
author_facet	O'Brien, C. Hutson, J. Olsen, T. Ratican, J.
author_sort	O'Brien, C.
title	Use of AI to Recreate and Repatriate Lost, Destroyed or Stolen Paintings: The 1785 Parisian Salon Case Study
title_short	Use of AI to Recreate and Repatriate Lost, Destroyed or Stolen Paintings: The 1785 Parisian Salon Case Study
title_full	Use of AI to Recreate and Repatriate Lost, Destroyed or Stolen Paintings: The 1785 Parisian Salon Case Study
title_fullStr	Use of AI to Recreate and Repatriate Lost, Destroyed or Stolen Paintings: The 1785 Parisian Salon Case Study
title_full_unstemmed	Use of AI to Recreate and Repatriate Lost, Destroyed or Stolen Paintings: The 1785 Parisian Salon Case Study
title_sort	use of ai to recreate and repatriate lost, destroyed or stolen paintings: the 1785 parisian salon case study
publisher	INTI International University
publishDate	2023
url	http://eprints.intimal.edu.my/1883/1/joit2023_21.pdf http://eprints.intimal.edu.my/1883/ http://ipublishing.intimal.edu.my/joint.html
_version_	1789946100726104064
score	13.211869

Use of AI to Recreate and Repatriate Lost, Destroyed or Stolen Paintings: The 1785 Parisian Salon Case Study

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