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D(A)NTE’S (I)NFERNO RAPPRESENTAZIONE DELL’INFERNO DANTESCO ATTRAVERSO TECNICHE DI DISEGNO INTEGRATO A.I. E PARAMETRICO.

Authors: Alessandro Basso; Caterina Palestini; Giovanni Rasetti; Maurizio Perticarini;

D(A)NTE’S (I)NFERNO RAPPRESENTAZIONE DELL’INFERNO DANTESCO ATTRAVERSO TECNICHE DI DISEGNO INTEGRATO A.I. E PARAMETRICO.

Abstract

The Divine Comedy is a narrative work of great imaginative power in which Dante Alighieri conveys otherworldly scenarios that come to life in an extremely vivid way; its description has offered artists in every historical period an inexhaustible source of inspiration, prompting them to capture the visual and symbolic essence of Dante's work. The proposed research aims to recover the diagrammatic tradition, transporting it to the contemporary through the use of artificial intelligence technologies and parametric drawing to reconstitute a virtual model of Dante's inferno. Text-to-image (DallE3, Midjourney, KreaAI, Flux, Stable Diffusion), text-to-3d (LumbasAI, Luma AI Genie) and image-to-3d (Rodin AI, 3DFY, Meshy, Alpha3D) AIs will be used synergistically to model Dante's territory. AI-generated images trained with input models derived from Dante's iconography, making use of text-to-image/image-to-image algorithms, will serve as a 3D matrix to generate semi-three-dimensional structures that will generate backdrops and soils, while Image-to-3d algorithms will provide three-dimensional elements that will be recomposed into the circles through generative processes and traditional 3D modeling and arranged through algorithmic-procedural methodologies.

Related Organizations
Keywords

AI remodelling, VR, Dante, Cultural Heritage, Real time Rendering

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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