{"id":168501,"date":"2023-06-08T16:00:00","date_gmt":"2023-06-08T15:00:00","guid":{"rendered":"https:\/\/liora.io\/en\/?p=168501"},"modified":"2026-08-09T18:23:38","modified_gmt":"2026-08-09T17:23:38","slug":"edit-your-photos-at-will-with-drag-your-gan","status":"publish","type":"post","link":"https:\/\/liora.io\/en\/edit-your-photos-at-will-with-drag-your-gan","title":{"rendered":"Edit Your Photos at Will With Drag Your GAN"},"content":{"rendered":"\n

With the advent of generative artificial intelligence, creative work are automated. Recently, a group of researchers created Drag Your GAN, an AI model capable of retouching images at will.<\/strong><\/p>\n\n\n

What Is Drag Your GAN?<\/h2>\n\n\n

Drag Your GAN is a deep learning AI model<\/a> called Generative Adversarial Networks (GAN)<\/strong>. Created by AI researchers from Google, the Max Planck Institute and MIT CSAIL, this team has devised an approach to dot-based modifications of realistic images<\/strong>.<\/p>\n\n\n

To achieve this, DYG uses two deep neural networks<\/a>, a generator and a discriminator, which work in opposition to each other to generate new synthetic images compared with the original. Besides these neural networks, the researchers designed DYG based on latent code optimization<\/a>, which enables them to move the image to the indicated location, while preserving its proportions and structure.<\/p>\n\n\n

Currently in the testing phase, the group hopes to extend its model to 3D modifications<\/strong> in the coming months.<\/p>\n\n\n

\"Illustration<\/figure>\n\n\n

How does Drag Your GAN work?<\/h2>\n\n\n

DYG<\/a> is a futuristic image editor<\/strong>. Far from replacing Photoshop, it will enable users to transform their photos easily at will. All you have to do is select two points, the start and end zones, and let the model do its thing<\/strong>. As a pre-trained model, DYG can only modify so-called realistic images, such as photos of humans, landscapes or animals. But it can also create textures<\/strong> such as teeth or eyes from scratch.<\/p>\n\n\n

\nhttps:\/\/vcai.mpi-inf.mpg.de\/projects\/DragGAN\/data\/DragGAN.mp4<\/a><\/video><\/div>\n\n\n

Building on their nascent success, GANs could well become the next blockbuster technology<\/strong> after generative AI. To carry out the research that will develop these next technologies, companies are investing heavily in teams of data professionals<\/strong>. So, if you’ve enjoyed this article and are considering a career in Data Science, don’t hesitate to check out our articles<\/a> or training offers<\/a> on Liora.<\/p>\n\n\n

Source : vcai.mpi-inf.mpg.de<\/i><\/p>\n\n","protected":false},"excerpt":{"rendered":"

With the advent of generative artificial intelligence, creative work are automated. Recently, a group of researchers created Drag Your GAN, an AI model capable of retouching images at will. What Is Drag Your GAN? Drag Your GAN is a deep learning AI model called Generative Adversarial Networks (GAN). Created by AI researchers from Google, the […]<\/p>\n","protected":false},"author":74,"featured_media":168503,"comment_status":"open","ping_status":"open","sticky":false,"template":"elementor_theme","format":"standard","meta":{"_acf_changed":false,"editor_notices":[],"footnotes":""},"categories":[2433],"class_list":["post-168501","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-data-ai"],"acf":[],"_links":{"self":[{"href":"https:\/\/liora.io\/en\/wp-json\/wp\/v2\/posts\/168501","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/liora.io\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/liora.io\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/liora.io\/en\/wp-json\/wp\/v2\/users\/74"}],"replies":[{"embeddable":true,"href":"https:\/\/liora.io\/en\/wp-json\/wp\/v2\/comments?post=168501"}],"version-history":[{"count":2,"href":"https:\/\/liora.io\/en\/wp-json\/wp\/v2\/posts\/168501\/revisions"}],"predecessor-version":[{"id":210799,"href":"https:\/\/liora.io\/en\/wp-json\/wp\/v2\/posts\/168501\/revisions\/210799"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/liora.io\/en\/wp-json\/wp\/v2\/media\/168503"}],"wp:attachment":[{"href":"https:\/\/liora.io\/en\/wp-json\/wp\/v2\/media?parent=168501"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/liora.io\/en\/wp-json\/wp\/v2\/categories?post=168501"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}