Karnewar was intrigued and promised her to try. “It was a very cool problem with an interesting application,” says the 23-year-old.

The relatability of the challenge appealed to him: he had the same issue imagining how Rachel, the protagonist of Paula Hawkins’ The Girl on The Train, looked. The result of the Pune-based engineer’s three-month experiment is entitled ‘Text to Face’ (T2F), which relies on a concept called Generative Adversarial Networks (GANs), introduced in 2014 by machine learning scholar Ian Goodfellow.

GANs consist of two networks — one called the generator, and the other the discriminator — which are pitted against each other. The discriminator ensures that it spots all fakes produced by the generator, while the generator ensures that what it produces is as close to the authentic version as possible.

Through a series of interactions, the rendered image is fine-tuned. But GANs need data to get to work.

Karnewar came across researchers at the University of Copenhagen and University of Malta, who were working on a project trying to achieve the reverse: Face to Text. On request, he received 400 randomly selected faces accompanied by text annotations. Read more from thehindu.com…

thumbnail courtesy of thehindu.com