4 Posts

Animation showing image-to-image style transfer — mapping process

AI With a Sense of Style: Style Transfer Method Produces Consistent Output in Successive Frames

The process known as image-to-image style transfer — mapping, say, the character of a painting’s brushstrokes onto a photo — can render inconsistent results. When they apply the styles of different artists to the same target
Makeup applied on female faces with the help of augmented reality

A Good Look for AI: How L’Oreal uses AI to power its virtual makeup try-on

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.
Examples of CT scans with different contrasts

More Data for Medical AI: AI recognizes medical scans without iodine dye.

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.
Examples of Generative Adversarial Networks used for image to illustration translation

Style and Substance: An improved GAN technique for style transfer

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.

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