Until now, all that could be made of the woman was the faintest trace of her outline. However, by using a neural network, computer scientists were able to bring the painting back to life.
, there is the faint figure of a woman. She was first detected in 1998, when conservators at the Art Institute of Chicago used X-rays and infrared light to peek behind the top layer of paint. She sits with her left arm reaching toward the viewer and her right arm tucked onto her lap—and curiously, she matches a sketch Picasso sent to a colleague around the same time.
Until now, all that could be detected of the woman was the faintest trace of her outline. Any extra detail—like color and style—was lost. However, by using a neural network trained to distinguish the style of one artist from another or of one period from another, researchers at University College London have given her a new life, even if it is not necessarily true to the Picasso original.
A neural network has helped reconstruct a lost work from Picasso's Blue Period, circa 1903. Credit: Anthony Bourached and George Cannat the University of Tübingen, Germany, called neural style transfer. The machine vision technique can identify the style of a painting and transform the style of a painting to match another. It can transform a Michelangelo into the style of Paul Cézanne, for example.
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