Posted on April 29, 2020
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Editing in Style - Uncovering the Local Semantics of GANs
Generative adversarial networks (GANs) are hugely popular for generating fake images. But a key topic is fine-grained editing and adjusting. I.e. you can generate a random person, but can you generate a random smiling person? To what degree can we edit these visual features of people?
This paper presents a mechanism by using reference images and regions and transferring them onto the generated images. Neat! And useful.
