Exposing White Supremacy: A.I. Edition

Joined
Jun 24, 2012
Messages
39,797
Reputation
-250
Daps
65,133
Reppin
NULL
While many think technology has helped generations of people with knowledge and information, the powers that be find ways of technology to control your life, viewpoint and actions while distracting you with entertainment and foolishness. They have devise a massive plan to control all viewpoints of perception with AI. AI will frame a person, introduce you to fabricated victims and show their story the way they want it. The future is scary as the next stages of White Supremacy begins.

NOT MY EXPRESSIONS!

AI is being used to reenact your facial expressions to either hurt or damage your credibility. Don't be surprised your statements are changed and put your every word out of context in real time.


TUM Visual Computing: Prof. Matthias Nießner

We present a novel approach for real-time facial reenactment of a monocular target video sequence (e.g., Youtube video). The source sequence is also a monocular video stream, captured live with a commodity webcam. Our goal is to animate the facial expressions of the target video by a source actor and re-render the manipulated output video in a photo-realistic fashion. To this end, we first address the under-constrained problem of facial identity recovery from monocular video by non-rigid model-based bundling. At run time, we track facial expressions of both source and target video using a dense photometric consistency measure. Reenactment is then achieved by fast and efficient deformation transfer between source and target. The mouth interior that best matches the re-targeted expression is retrieved from the target sequence and warped to produce an accurate fit. Finally, we convincingly re-render the synthesized target face on top of the corresponding video stream such that it seamlessly blends with the real-world illumination. We demonstrate our method in a live setup, where Youtube videos are reenacted in real time.






Changing of Night/Day/Time of Day ....With this technology AI can help Police/Law Enforcement fabricate their dirt by changing the enviroment around you. Don't expect body or dash-cams to show you proof of lies on their end. Expect AI to take over and the demons to fill in the story-line.

https://petapixel.com/2017/12/05/ai-can-change-weather-seasons-time-day-photos/
seaonchangefeat-800x420.jpg


snow00000206-800x302.jpg




I0151-800x302.jpg




Fake Celebrities but also fake people

When a mass casualty event happens again, best believe this has been or can be used. A black celebrity or athlete accused of rape, this AI can create a victim out of thin-air.

Nvidia's AI machine generates fake faces from celebrity images

A new artificial intelligence created by Nvidia recently spat out a wild diversity of fake faces after researchers fed it thousands of real celebrity photos.
The graphics chip company is currently experimenting with a new method of training AI to generate novel faces using real photos. Nvidia researchers published their somewhat creepy results online and submitted them to the International Conference on Learning Representations 2018.
The research team admitted their AI-spawned faces still leave "a lot to be desired," but confidently pointed out that "we feel that convincing realism may now be within reach."
Although their work still awaits review from other AI experts, the researchers were pleased with both the variety of faces their machine generated and the nuanced detail achieved in 1,024-pixel resolution, which can be seen in the video above.
They used an increasingly popular AI training system called a general adversarial network (GAN). The program is fed a massive data set — in this case celebrity photos — and then gets better at creating the desired result (in this case, realistic computer-generated faces) over a period of days or weeks. The "adversarial" component involves pitting two machine-learning programs against one another, with one program "challenging" the other's face creations.
The future applications of rendering realistic looking people — that aren't actually people — seems both potentially useful and unsettling. This is certainly a boon to graphics companies that always need new images of people, perhaps for use in advertising. But it's also important to recognize AI-programs are getting closer and closer to achieving realism in artificial faces; how this might be employed in fake news and other means of deception is unknown — and boundless. For now, though, it's at least given us some really interesting faces to look at.

 

scarlxrd

Underground
Supporter
Joined
Nov 8, 2014
Messages
13,860
Reputation
7,774
Daps
54,609
Changing of Night/Day/Time of Day ....With this technology AI can help Police/Law Enforcement fabricate their dirt by changing the enviroment around you. Don't expect body or dash-cams to show you proof of lies on their end. Expect AI to take over and the demons to fill in the story-line.
This AI is supposed to wash raw data from body cams? That's terabytes of storage. The video you linked looks like screenshots, are you saying they're going to use this on TBs of data?
 

scarlxrd

Underground
Supporter
Joined
Nov 8, 2014
Messages
13,860
Reputation
7,774
Daps
54,609
They could. All you need to do is upload the footage on to a computer with the AI technology.
:russ: Breh, no.

The sample isn't raw. It's sub-HD 480p using maybe 5-10 FPS. That's why the video looked like screenshots. It's just a tech demo.

Qualitative results. Figure 3 to 6 showed results of the proposed framework on various UNIT tasks. Street images. We applied the proposed framework to several unsupervised street scene image translation tasks including sunny to rainy, day to night, summery to snowy, and vice versa. For each task, we used a set of images extracted from driving videos recorded at different days and cities. The numbers of the images in the sunny/day, rainy, night, summery, and snowy sets are 86165, 28915, 36280, 6838, and 6044. We trained the network to translate street scene image of size 640×480. In Figure 3, we showed several example translation results . We found that our method could generate realistic translated images. We also found that one translation was usually harder than the other. Specifically, the translation that required adding more details to the image was usually harder (e.g. night to day). Additional results are available in GitHub - mingyuliutw/UNIT: unsupervised/unpaired image-to-image translation using coupled GANs.

Look at their github, it's not as advanced as you're making it out to be.

Like they having been doing this shyt for years
:dead: Yeezus
 
Joined
Jun 24, 2012
Messages
39,797
Reputation
-250
Daps
65,133
Reppin
NULL
:russ: Breh, no.

The sample isn't raw. It's sub-HD 480p using maybe 5-10 FPS. That's why the video looked like screenshots. It's just a tech demo.



Look at their github, it's not as advanced as you're making it out to be.


:dead: Yeezus


Obviously you weren't paying attention.... I said this is used in future purposes. Of course it's a demo.
 
Top