Generative Adversarial Network Special

5 Posts

Makeup applied on female faces with the help of augmented reality
Generative Adversarial Network Special

A Good Look for AI

Trying on new makeup is a hassle — apply, inspect, wash off, repeat. Not to mention the tribulation of visiting brick-and-mortar stores during the pandemic. Augmented reality is helping people try on all the makeup they want without leaving home.
2 min read
Data and examples related to IMLE-GAN
Generative Adversarial Network Special

Making GANs More Inclusive

A typical GAN’s output doesn’t necessarily reflect the data distribution of its training set. Instead, GANs are prone to modeling the majority of the training distribution, sometimes ignoring rare attributes — say, faces that represent minority populations.
2 min read
Examples of CT scans with different contrasts
Generative Adversarial Network Special

More Data for Medical AI

Convolutional neural networks are good at recognizing disease symptoms in medical scans of patients who were injected with iodine-based dye, that makes their organs more visible. But some patients can’t take the dye. Now synthetic scans from a GAN are helping CNNs learn to analyze undyed images.
2 min read
Data and examples related to a new technique to detect portions of an image
Generative Adversarial Network Special

The Telltale Artifact

Deepfakes have gone mainstream, allowing celebrities to star in commercials without setting foot in a film studio. A new method helps determine whether such endorsements — and other images produced by generative adversarial networks — are authentic.
2 min read
Examples of Generative Adversarial Networks used for image to illustration translation
Generative Adversarial Network Special

Style and Substance

GANs are adept at mapping the artistic style of one picture onto the subject of another, known as style transfer. However, applied to the fanciful illustrations in children’s books, some GANs prove better at preserving style, others better at preserving subject matter.
2 min read

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