State of the GAN: состязательные сети. Лекция 3
Лекция- Математика
GAN’ы для обработки изображений
Одна из основных областей, где применяются GAN’ы — это обработка и содержательное изменение изображений (image manipulation). Как состарить фото человека, как сделать deepfake, как — всё это модели, основанные на GAN’ах. Мы поговорим об условных GAN’ах, на примере задачи переноса стиля (style transfer) поговорим о прогрессе image-to-image архитектур, обсудим и face swap модели, то бишь deepfakes. А ещё я расскажу о двух работах в этом направлении, которые были недавно сделаны в Samsung AI Center.
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![Аватар пользователя Davidjohn34 Аватар пользователя Davidjohn34](/sites/lektorium.tv/files/avatar_selection/lomonosov.jpg)
The idea behind adversarial training is that you give the model an example and then ask it to generate an example that is similar but not exactly the same as the example it was given. This way, you can train your model to weaver game generate examples that are biased in one direction or another.
![Аватар пользователя Davidjohn34 Аватар пользователя Davidjohn34](/sites/lektorium.tv/files/avatar_selection/lomonosov.jpg)
The idea behind adversarial training is that you give the model an example and then ask it to generate an example that is similar but not exactly the same as the example it was given. This way, you can train your model to weaver game generate examples that are biased in one direction or another.
![Аватар пользователя Davidjohn34 Аватар пользователя Davidjohn34](/sites/lektorium.tv/files/avatar_selection/lomonosov.jpg)
The idea behind adversarial training is that you give the model an example and then ask it to generate an example that is similar but not exactly the same as the example it was given. This way, you can train your model to weaver game generate examples that are biased in one direction or another.