{"id":29895,"date":"2019-10-31T21:32:30","date_gmt":"2019-10-31T18:32:30","guid":{"rendered":"https:\/\/prohoster.info\/blog\/nejroset-ot-nvidia-prevrashhaet-prostejshie-nabroski-v-krasivye-pejzazhi\/"},"modified":"2019-10-31T21:32:30","modified_gmt":"2019-10-31T18:32:30","slug":"nejroset-ot-nvidia-prevrashhaet-prostejshie-nabroski-v-krasivye-pejzazhi","status":"publish","type":"post","link":"https:\/\/prohoster.info\/en\/blog\/nejroset-ot-nvidia-prevrashhaet-prostejshie-nabroski-v-krasivye-pejzazhi","title":{"rendered":"Nvidia's neural network transforms simple sketches into beautiful landscapes","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"

\"Nvidia's
\nThe smoker's waterfall and the healthy person's waterfall<\/p>\n

We all know how to draw an owl. First, you draw an oval, then another circle, and then \u2014 you get a magnificent owl. Of course, that's a joke, and quite an old one, but Nvidia engineers have worked hard to make imagination a reality. <\/p>\n

New development<\/a><\/noindex>, called GauGAN, creates stunning landscapes from very simple sketches (really simple \u2014 circles, lines, and all). Of course, modern technologies are at the heart of this development \u2014 namely, generative adversarial neural networks.
\n<\/a><\/noindex>
\nGauGAN allows you to create colorful virtual worlds \u2014 not only for entertainment but also for work. Architects, landscape designers, game developers \u2014 they can all gain something useful. The artificial intelligence instantly \"understands\" what a person wants and supplements the initial idea with a wealth of details. <\/p>\n

\"Brainstorming in design development becomes much easier with the help of GauGAN, as the smart brush can enhance the original sketch by adding high-quality images,\" said one of the developers of GauGAN.<\/p>\n

Users of this tool can modify the original idea, alter the landscape or other images, adding sky, sand, water, and so on. Everything that the soul desires, and the addition happens in just a couple of seconds.<\/p>\n

The neural network was trained using a database of millions of images. Thanks to this, the system can understand what a person wants and how to achieve the desired result. Moreover, the neural network does not forget about the tiniest details. So, if you sketch a pond and some trees nearby, when the landscape comes to life, all nearby objects will be reflected in the pond's water.<\/p>\n

The system allows you to specify what the visible surface should be \u2014 it can be covered with grass, snow, water, or sand. All this can be transformed in a second, so snow becomes sand, and instead of a snowy wasteland, the artist gets a desert landscape. <\/p>\n

\u201cIt's like a coloring book that tells you where to place the tree, where the sun goes, and where the sky is. Then, after the initial task, the neural network brings the picture to life, adding necessary details and textures, and rendering reflections. All of this is based on real images,\u201d says one of the developers. <\/p>\n

\r\n \"Play\r\n
<\/div>\r\n <\/div><\/center>
\nAlthough the system lacks a \u201cunderstanding\u201d of the real world, it creates impressive landscapes. This is because it uses two neural networks: a generator and a discriminator. The generator creates an image and shows it to the discriminator, which, based on millions of previously seen images, selects the most realistic options. <\/p>\n

That's why the generator \u201cknows\u201d where reflections should be. It is worth noting that the tool is quite flexible and comes with many settings. For example, it can produce paintings tailored to the style of a particular artist or simply allow for quick additions like a sunrise or sunset. <\/p>\n

Developers claim that the system doesn't simply take images from somewhere, combine them, and produce a result. No, all the obtained \u201cpictures\u201d are generated. In other words, the neural network \u201ccreates\u201d like a real artist (or even better).<\/p>\n

Currently, the program is not available to the public, but soon it will be possible to try it out in action. This will be possible at the GPU Technology Conference 2019, which is currently taking place in California. Lucky attendees who were able to visit the conference can already test GauGAN.<\/p>\n

Neural networks have long been learning to participate in the creative process. For example, last year, some of them were able to create 3D models<\/a><\/noindex>. Additionally, developers from DeepMind trained a neural network to restore three-dimensional spaces and objects from drawings, photos, and sketches. To recreate a simple shape, the neural network needs just one image; for more complex objects, five images are required for \u201ctraining.\u201d<\/p>\n

As for GauGAN, this tool will clearly find valuable commercial applications \u2014 many business and scientific fields have a need for such services.<\/p>\n

Source: habr.com<\/a><\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"

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(\u0434\u0435\u0439\u0441\u0442\u0432\u0438\u0442\u0435\u043b\u044c\u043d\u043e […]<\/p>\n","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[],"tags":[],"class_list":["post-29895","post","type-post","status-publish","format-standard","hentry"],"aioseo_notices":[],"aioseo_head":"\n\t\t\n\t\n\t\n\t\n\t\n\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\n","aioseo_head_json":{"title":"\ud83e\udd47Nvidia's neural network transforms simple sketches into beautiful landscapes | ProHoster","description":"The smoker's waterfall 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