Research Article

AI-Generated Artwork as a Modern Interpretation of Historical Paintings

Wai Yie Leong 1 2 2 *
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1 INTI International University2 Schneider Electric Singapore* Corresponding Author
International Journal of Social Sciences and Artistic Innovations, 5(1), 2025, 0002, https://doi.org/10.35745/ijssai2025v05.01.0002
Submitted: 03 November 2024, Published: 08 March 2025
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ABSTRACT

The intersection of artificial intelligence (AI) and art offers unprecedented opportunities to reinterpret historical paintings, bringing classical masterpieces into a modern visual context. This paper explores the application of AI, particularly generative models such as Generative Adversarial Networks (GANs) and neural style transfer, to create contemporary interpretations of iconic historical artworks. By leveraging large datasets of classical paintings, AI systems are trained to analyze and replicate stylistic features, reimagining compositions while preserving the essence of the original works. Our study presents a systematic analysis of the generated artworks, evaluating their fidelity, visual quality, and cultural resonance through both quantitative metrics and viewer surveys. Comparisons are drawn between different AI models to assess their effectiveness in style preservation and content adaptation. The results indicate that AI-generated reinterpretations can bridge historical and modern artistic practices, offering novel ways to experience and engage with classical art. This research highlights the potential of AI as a transformative tool in art conservation, education, and exhibition, while also addressing the ethical implications of AI in recreating culturally significant works.
Keywords: Artificial Intelligence (AI), historical paintings, Generative Adversarial Networks (GANs)

CITATION (APA)

Leong, W. Y. (2025). AI-Generated Artwork as a Modern Interpretation of Historical Paintings. International Journal of Social Sciences and Artistic Innovations, 5(1), 0002. https://doi.org/10.35745/ijssai2025v05.01.0002

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