"This work explores how a feedback loop of generative adversarial neural networks (GANs) is transforming errors into meaning while at the same time confirming and emphasizing biases in the training data. Three GANs and a camera form a closed chain in which they interpret and transform the input they receive amongst each other. Each model has been trained on thousands of painted "old masters" portraits harvested from various European collections. One model's purpose is to generate a biometric semantic map of all faces found in an image, another model translates these maps back into portraits, a third model adds details and texture to the result. A camera filming the artist is mixed into the loop in varying degrees, disturbing and changing the face markers." 79530 Self Portrait Ars Electronica retrieved June 12, 2019
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Country
Germany
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Description (in English)
Situation machine vision is used in
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UUID
4c4d9098-e4ac-4e0e-8da1-1f9cc9626128