Generative AI, mainly through Diffusion Models, has revolutionized art creation, blurring the distinction between human and AI-generated art. This study introduces a novel dataset comprising human-made and AI-generated art and employs Deep Learning models (VGG-19, ResNet-50, ViT) to distinguish between them. We also use eXplainable AI techniques to derive insights. Our results highlight the potential of AI to detect machine-generated content, with implications for art authentication.
Identifying AI-Generated Art with Deep Learning
Tommaso Bianco;Giovanna Castellano;Raffaele Scaringi
;Gennaro Vessio
2023-01-01
Abstract
Generative AI, mainly through Diffusion Models, has revolutionized art creation, blurring the distinction between human and AI-generated art. This study introduces a novel dataset comprising human-made and AI-generated art and employs Deep Learning models (VGG-19, ResNet-50, ViT) to distinguish between them. We also use eXplainable AI techniques to derive insights. Our results highlight the potential of AI to detect machine-generated content, with implications for art authentication.File in questo prodotto:
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