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Reimagining Benin Bronzes using generative adversarial networks.
- Source :
- AI & Society; Feb2024, Vol. 39 Issue 1, p91-102, 12p
- Publication Year :
- 2024
-
Abstract
- In this paper, I describe my artistic project, Igùn—a StyleGAN series trained to animate the research question: what bronze objects could have been produced should the 1897 British invasion not have occurred in the Benin Kingdom? In addition to looting over 3000 palace-commissioned artworks, I surmise that the invasion resulted in a 17-year (1897–1914) artistic decline. Although post-invasion colonial reports referred to a thriving art scene and increased colonial art patronage, there is a dearth of visual documentation to identify objects created during this period. Considering this absence, I propose Igùn, a series of StyleGAN models trained on a dataset of looted Benin Bronzes. This project is informed by the Igún Eronmwon's (the royal guild of bronze casters) artistic protocols. Finally, I present three prototypes based on emergent themes—infancy and facial expressions, which were underexplored in Benin's classical bronze casting tradition. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 09515666
- Volume :
- 39
- Issue :
- 1
- Database :
- Complementary Index
- Journal :
- AI & Society
- Publication Type :
- Academic Journal
- Accession number :
- 175388582
- Full Text :
- https://doi.org/10.1007/s00146-023-01761-7