# DeepMind’s New AI Dreams Up Videos on Many Topics

## Метаданные

- **Канал:** Two Minute Papers
- **YouTube:** https://www.youtube.com/watch?v=IMZkLVBhcig
- **Дата:** 27.08.2019
- **Длительность:** 3:26
- **Просмотры:** 72,394

## Описание

📝 The paper "Efficient Video Generation on Complex Datasets" is available here:
https://arxiv.org/abs/1907.06571

❤️ Pick up cool perks on our Patreon page: https://www.patreon.com/TwoMinutePapers

🙏 We would like to thank our generous Patreon supporters who make Two Minute Papers possible:
313V, Alex Haro, Andrew Melnychuk, Angelos Evripiotis, Anthony Vdovitchenko, Brian Gilman, Bruno Brito, Bryan Learn, Christian Ahlin, Christoph Jadanowski, Claudio Fernandes, Daniel Hasegan, Dennis Abts, Eric Haddad, Eric Martel, Evan Breznyik, Geronimo Moralez, James Watt, Javier Bustamante, John De Witt, Kaiesh Vohra, Kasia Hayden, Kjartan Olason, Levente Szabo, Lorin Atzberger, Lukas Biewald, Marcin Dukaczewski, Marten Rauschenberg, Maurits van Mastrigt, Michael Albrecht, Michael Jensen, Nader Shakerin, Owen Campbell-Moore, Owen Skarpness, Raul Araújo da Silva, Rob Rowe, Robin Graham, Ryan Monsurate, Shawn Azman, Steef, Steve Messina, Sunil Kim, Taras Bobrovytsky, Thomas Krcmar, Torsten Reil, Zach Boldyga.
https://www.patreon.com/TwoMinutePapers

Splash screen/thumbnail design: Felícia Fehér - http://felicia.hu

Károly Zsolnai-Fehér's links:
Instagram: https://www.instagram.com/twominutepapers/
Twitter: https://twitter.com/karoly_zsolnai
Web: https://cg.tuwien.ac.at/~zsolnai/

## Содержание

### [0:00](https://www.youtube.com/watch?v=IMZkLVBhcig) Segment 1 (00:00 - 03:00)

dear fellow scholars this is two minute papers with károly fajir in the last few years the pace of progress in machine learning research has been staggering neural network based learning algorithms are now able to look at an image and describe what's seen in this image or even better the other way around generating images from a written description you see here a set of results from began a state-of-the-art image generation technique and marvel at the fact that all of these images are indeed synthetic the GAM part of this technique abbreviates the term generative adversarial network this means a pair of neural networks that battle each other over time to master a task for instance to generate realistic looking images when given a theme these detailed images are great but what about generating video with the dual video discriminator again DVD gain in short deep Minds naming game is still as strong as ever it is now possible to create longer and higher resolution videos than was previously possible the exact numbers are 256 by 256 in terms of resolution and 48 frames which is about 2 seconds it also learned the concept of changes in the camera view zooming in on an object and understands that if someone draws something with a pen the ink has to remain on the paper and changed the dual discriminator part of the name reveals one of the key ideas of the paper in a classical again we have a discriminator network that looks at the images of the generator network and critiques them as a result the discriminator learns to tell fake and real images apart better but at the same time provides ample feedback for the generator neural network so it can come up with better images in this work we have not one but two discriminators one is called the spatial discriminator that looks at just one image and assesses how good it is structurally while the second temporal discriminator critiques the quality of movement in these videos this additional information provides better teaching for the generator which in return be able to generate better videos for us the paper contains all the details that you could possibly want to learn about this algorithm in fact let me give you two that I found to be particularly interesting one it does not get any additional information about where the foreground and the background is and is able to leverage the learning capacity of these neural networks to learn these concepts by itself and two it does not generate the video frame by frame sequentially but it creates the entire video in one go that's wild now 256 by 256 is not a particularly high video resolution but if you have been watching this series for a while you are probably already saying that two more papers down the line and we may be watching HD videos that are also longer than we have the patience to watch and all this through the power of machine learning research for now let's applaud deepmind for this amazing paper and I can't wait to have a look at more results and see some follow-up works on it what a time to be alive thanks for watching and for your generous support and I'll see you next time

---
*Источник: https://ekstraktznaniy.ru/video/14262*