Nvidia’s New AI Can Generate Mind-Blowing Fake Videos
Subscribe:  iCal  |  Google Calendar
7, Mar — 12, Jun
San Francisco US   19, Mar — 24, Mar
Anaheim US   23, Mar — 26, Mar
San Jose US   26, Mar — 30, Mar
Washington US   30, Mar — 2, Apr
Latest comments
by badminton rackets
19 min ago

Wonderful illustrated information. I thank you about that. No doubt it will be very useful for my future projects. Would like to see some other posts on the same subject! badminton rackets

by rayen
48 min ago

that's all nice but what's the purpose of that there is no consumer hardware that can't handle that in real game enviroment

by Romain
1 hours ago

Yeah I know normally a friendly artist is planning to make one about it

Nvidia’s New AI Can Generate Mind-Blowing Fake Videos
6 December, 2017

Nvidia has recently presented an AI that with an unsupervised learning method for computers which can create mind-blowing fake videos. The system will allow users to set up weather, turn day into night, and change almost anything. 

Previous techniques relied on massive amounts of data and has problems with training the machines to find their own patterns. Researched had a hard time dealing with mapping a low-resolution image to a corresponding high-resolution image and colorization (mapping a gray-scale image to a corresponding color image).

Unsupervised image-to-image translation aims at learning a joint distribution of images in different domains by using images from the marginal distributions in individual domains. Since there exists an infinite set of joint distributions that can arrive the given marginal distributions, one could infer nothing about the joint distribution from the marginal distributions without additional assumptions. To address the problem, we make a shared-latent space assumption and propose an unsupervised image-to-image translation framework based on Coupled GANs. We compare the proposed framework with competing approaches and present high quality image translation results on various challenging unsupervised image translation tasks, including street scene image translation, animal image translation, and face image translation. We also apply the proposed framework to domain adaptation and achieve state-of-the-art performance on benchmark datasets. Code and additional results are available in this https URL .

Ming-Yu LiuThomas BreuelJan Kautz 

Read the paper

The modern machines can turn sunny days into rainy ones, create the equivalent of a “snow plow” filter for videos, and more. 

Reality is now a strange thing thanks to projects of Nvidia. Should we be worried? Let’s discuss!

Leave a Reply

Be the First to Comment!