Through DragGAN, anyone can deform an image with precise control over where pixels go
The timeline traces deep learning model milestones starting from the beginning of the “AI summer” in 2012.
A Screen Walks playlist of recorded live-streamed events touching on machine learning.
Using generative adversarial networks (GAN), we can learn how to create realistic-looking fake versions of almost anything, as shown by this collection of sites.
Generated Photos 100,000 Faces Generated by AI Free to Download These people aren’t real! We are building the next generation of media through the power of AI (an original machine learning …
DeepPrivacy A fully automatic anonymization technique for images. This repository contains the source code for the paper “DeepPrivacy: A Generative Adversarial Network for Face …
6,295 Likes, 608 Comments - Bill Posters (@bill_posters_uk) on Instagram: “‘Imagine this...’ (2019) Mark Zuckerberg reveals the truth about Facebook and who really owns the…”
Fortunately we are smart people and have found a way out of this predicament. Instead of relying on algorithms, which we can be accused of manipulating for our benefit, we have turned to machine …
Snapchat's new gender-bending filter is a source of endless fun and laughs at parties. The results are very pleasing to look at. As someone ...
Mike Tyka, Dreams of Imaginary People, 2017 (constantly morphing hypnotic GAN portraits)
mario-klingemann: ChainGAN portrait series by Mario Klingemann