StyleGAN2

[Veedrac]

I set up this super simple ‘Which Face Is Real?’ (http://www.whichfaceisreal.com/) style challenge. Click the row to show the answers. You might need to zoom out.

https://veedrac.github.io/stylegan2-real-or-fake/game.html

There's a harder version as well, where the image is zoomed in.

https://veedrac.github.io/stylegan2-real-or-fake/game_croppe...

I get 100% reliably with the first link (game.html), and got 4/5 on the cropped version (game_cropped.html) so far.

[ebg13]

> I get 100% reliably with the first link, and got 4/5 on the cropped version so far.

Looking at whichfaceisreal, How much time do you have to spend on each decision, and would your success rate change if you didn't know in advance that exactly 1 of 2 was generated? It's easy to say 100% reliable, but I find myself really having to dig deep with my eyes to search for small tells* , which you have to know to do up front before you actually do it.

* - Often the tells are as minuscule as some ringing around the hair, which could just as easily be compression artifacts on a real photo.

[echelon]

> I set up this super simple ‘Which Face Is Real?’ (http://www.whichfaceisreal.com/) style challenge.

GANs still don't get teeth right. If any artificial face smiles, the teeth are a dead giveaway.

[ImminentFate]

On your site I can consistently get 100% by looking at the backgrounds since they generate in somewhat inorganic patterns.

[gwd]

Only watched the video, but one of the interesting things is the potential method to tell a generated image from a real one: namely, if you take a generated image, it's possible to find parameters which will generate exactly the same image. But if you take a real image, it's generally not possible to get exactly the same image, but only a similar one.

The exact point in the video:

https://youtu.be/c-NJtV9Jvp0?t=208

[gwd]

Also, looks like https://thispersondoesnotexist.com/ has been updated to use the new generator.

[TeeWEE]

This is only possible if you have access to the model neural net... If you dont you cant tell the difference.

[resiros]

The demo in the official video is mind blowing. https://www.youtube.com/watch?v=c-NJtV9Jvp0 I wonder when we will see full movies unrecognizable from real ones made from deep learning.

[globuous]

Insane the part where they get multiple angles from the same generated face

[alexcnwy]

The part of the video showing the location bias in phase artifacts (straight teeth on angled faces) is really interesting and very clear in retrospect if you look at StyleGAN v1 outputs.

Their “new method for finding the latent code that reproduces a given image” is really interesting and I’m curious to see if it plays a role in the new $1 million Kaggle DeepFakes Detection competition.

It feels like we’re almost out of the uncanny valley. It’s interesting to place this in context and think about where this technology will be a few years from now - see this Tweet by Ian Goodfellow on 4.5 years of GAN progress for face generation: https://twitter.com/goodfellow_ian/status/108497359623614464...

[anonfunction]

I'm surprised to see Nvidia hosting[1] the pre-trained networks on google drive which has already been blocked for going over the quota:

> Google Drive download quota exceeded -- please try again later

1. https://github.com/NVlabs/stylegan2#using-pre-trained-networ...

[anyzen]

A bit off-topic - the license [0] is interesting. IIUC, if anyone who is using this code decides to sue NVidia, the grants are revoked, and they can sue back for copyright infringement?

Also, interesting that even with such "short" licences there are trivial mistakes in it (section 2.2 is missing, though it is referenced from 3.4 and 3.6 - I wonder what it was...)

[0] https://nvlabs.github.io/stylegan2/license.html

[supermatt]

Patent grants.

Its a butchered Amazon Software License: https://aws.amazon.com/asl/

[tiborsaas]

Imagine when these faces start talking, tracking objects with their eyes with a perfectly synthesized voice all, generated in real time.

[gdubs]

Of course we’ll hit a wall at some point, but when this repo dropped the other night and I saw the rotating faces in the video, it made me realize that in the future, VR experiences might be generated with nets rather than modeled with traditional CG.

[sails]

Any good resources for using GANs to generate synthetic tabular data?

[narsk]

ctfu at the car images. I made a twitter bot to tweet them out with fake make/model names https://twitter.com/bustletonauto

[nalllar]

urgh, custom CUDA ops now.

Original StyleGAN worked on AMD cards, this won't without porting those.

):

[jdkdnfndnfjd]

It makes me feel ill to see computers doing things like this. Aidungeon was difficult to stomach as well. GANs were invented on a whim by a single person. Nobody thought it would work when applied to this kind of problem. It came out of nowhere. Pretty soon someone will try something on a higher order task and it’s going to work. We are opening Pandora’s box and I’m not sure that we should do that.

[allenbrunson]

okay, i'll be the one to stick my neck out ...

i read a few of the AI Dungeon transcripts. i think it's worthless. you type in a command, like you would with an actual infocom-style adventure game, and it spits out a bunch of flowery language and gobbledygook, the likes of which you can get in abundance from any self-help guru. there is no state, no way to win, no way to lose. to compare it to actual adventure games is ludicrous.

likewise, i have yet to see anything having to do with StyleGAN photo manipulation that goes very far beyond the level of a parlor trick.

this stuff is going to appeal to the same people who love cryptocurrencies, and will have about the same level of real-world effect.