Reimagining Benin Bronzes using generative adversarial networks

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.