Computer Generates Human Faces 

The most important aspect of a face: shirt color.

I will have horrible nightmares from this

is this the yearbook of Chernobyl High?

7:33 "Let her head be Large...." **Eye pops out** "...or actually just give her a smaller head"

*_Nightmare Generator_*

I think it’s interesting that slider 2, male/female, also controls smile/frown so that males frown and females smile.

FIRST!!! It's amazing how each slider is so logical and describable, when you're sliding them around it almost feels like you're customizing your player in The Sims. But it was all chosen by a computer? Whhhhaaaaatttt 8:06

“Well I’m not sure, I can’t tell what this is doing, but it’s doing something” Basically every invention/discovery ever And also a quote from my uncle describing his dog

5:54 If you want an average person you get nothing

8:38 - That ended up being super clear!

The next step is is get a bunch of people to rate the attractiveness of each face and see how attractiveness correlates to each of those sliders. Maybe we don't realise but a slider that changes very little has a large effect on how we perceive that face!

5:55 Moral from the video: An *average* person is nobody. Be someone.

Yesterday was nostalgic. The future is unprecedented.

They Have No Eyes

6:55 was lateral facial symmetry. As the slider went more to one side that side of the face became larger in features compared to the other side. Maybe a shortened name would be something like 'facial slant' or something like that.

Computer Generates Human Faces... 10 years after car crash

Try using mugshots instead and you actually could make a police sketching thing. Though I suppose the head position of the suspect wont matter too much

meanwhile in 2023: you can animate donald trump catching an octopus and innviting his president friends to dinner

This video gives me a reason to learn more math.

I miss the times when this was a breakthrough

Several of you have asked for a way to play with the sliders yourselves. I'd love to provide that, but its a little tricky. First of all, the data set is not public and there are privacy concerns with releasing it. Second this demo currently has dependencies with python and other ML libraries that require a GPU that take a lot of machine-specific setup, definitely something too difficult for the average person. Another idea is to provide a web interface, but I don't have any experience with designing interactive web GUIs, I'm not much of a web guy. If someone out there IS a web developer and is willing to remake a GUI and host this on their site, then I could provide the backend and make this accessible to everyone.

this is actually kind of creepy looking at those faces

The Sims: Pripyat edition.

6:10 “Obviously, hair length is highly correlated to gender” Me, a long haired guy: Damn

8:55 wtf is that

I didn't understand a single thing, but still watched it till the end.

Would love to see a higher resolution version of this

It's amazing how it's been only 3 years but we've already advanced AI to the point where generated faces are near perfect!

This would be great for a horror game, good project though.

Is there a way to train a model to score how realistic a face is and use it to tweak the sliders using genetic algorithm?

This is just a video of Oblivion's character editor...

About half a decade later and modern AI has completely trivialized this process

I definitely think that you should continue making videos like this one.

In just a few years we went from this to stable diffusion/dalle 2/midjourney.

Here from carykh! You totally deserve more subs!

7:47 that is so freaking creepy

This could improve a lot how police sketches are created. Not only that, this provides an interface that could be used with NLP to automatically generate a seed sketch and then refined. Congratulations, really cool.

"I'm not sure what the format of this channel will be.": You're doing great. You keep it theoretically sound and practical so we can learn ourselves with your code.

The weird moment when you see your own face in the video

Number 8 is (a)symmetry y. It's easier to recognize if you don't think of these as faces but as images.

I want an online face generator for the world to use

These faces were truly horrific. Just stumbled upon your channel. Please dont dissapoint me by becoming inactive but instead you have lots of new amazing content like this one! :)

Me: *watches technical part* Brain: "oh, I totally understand this..." Me: "what did I just watch?" Brain: "ummmmmmmmmmmm what?"

I love that you went into the statistics a bit. Really cool concepts hiding in there.

8:22 Zucc shedding his skin

Incredible how far we’ve come since this

7:27 "Let's say we want someone with a dark shirt" "Female" Game over

Very intuitive presentation of ideas. The combination of Auto encoder with PCA to make them interpretable was new to me, even though I have read about VAE etc etc. Also your ability to interpret and label the first 8 or 10 features was mind blowing. Nice work!

This is one of the coolest, most inspiring videos I've seen in a long time. I really like what you do and what your interests are and seriously hope you're putting your skills and talent to good use in a challenging job. P.S. Where did you learn all this stuff? I learned about PCA just last year and was amazed at what it could do, but I'm referring to the programming skills.

This video is so cool. The explanation about PCA and what the most important features are using the slides is really educational. Thanks for putting this together.

Can you post the code on git I want to test this on my own dataset. Want to see where I stand in the customization of the sliders lol

Great video. I'd love to see more similar technical videos, with unsupervised learning. Seems like supervised learning dominates almost everything, but those things seem quite powerful. I'd love to see e.g. some variational eutoencoder or similar things.

at 2:49 what do you mean by "instead we just imbed all training samples randomly"? I understand what the latent space is. But if it's only 80 dimensions, how do you get an entire image down to those 80 dimensions without an encoder? Are you feeding a random vector into the latent space and training it to produce a face from just random inputs?

I generate a human face everytime i look in the mirror

Really cool! I guess my main question would be something like: how well can you recognise (parts of?) your high school classmates in the generated faces? Do they look like total strangers to you, or are most of them like "oh, that generated face is mostly just Peter, but with some variations" or maybe "that face is part Peter, part George"? The sliders seem to show a pretty smooth transition between faces, so I assume the former ... but at the same time, it's hard to judge how random they are without having known any of the people in the training set. Once again, really cool video! :)

7:33 / 7:34 Honestly, that right there looks really solid in comparison to most of the other faces in the video

I accidentally click the random button then a beautiful girl shows up. I clicked it again its lost

The demo is crazy fun to play with....

I have absolutely no clue what the hell is going on in this video but I'm hooked anyway

All that time in linear algebra and I literally couldn't visualize the shit we did when dicking around with bases or linear independence. It took this video to even get me a foothold two years later.

I was able to kindda replicate the concept your project. A rather poor man's version of it. My version is built with Tensorflow and Python, but I have a AMD GPU, so I had to make some sacrifices to be able to have interesting results with my CPU. Ended up scaling things down to 60x60 grayscale image. I don't know much academic level math, took me a while, but managed to grasp an intuitive understanding of PCA (and most importantly, implement it in python). As in your video, it made everything better. One thing I added to your concept was a couple randomizer buttons that switch all component values to +/-1 standard deviation, +/-2 standard deviation or +/-3 standard deviation it was really fun to see the generation of faces. I am afraid that in my search of scaling things down I might have overfitted the NN. My NN has an input of 3600 grayscale pixels (60x60 image), only one hidden layer of around 1000, and 40 dimensions in latent space. For training I used just 256 pictures , in batches of 16 pictures. For each epoch of training, I shuffled the training set, so that no 16 pictures batches the same, so to not have the same batches. I noticed this made a huge impact in quality of face generation. For optimizer I used a RMSPropOptimizer, learning step of 0.001 ,and for loss calculation, I tryied a few. I made several runs but all of them ended up simmilar. They didn't reduce loss over time. I also notice that some knob configurations produce really detailed images that I think are the same as one in the dataset. I am in doubt about it being overfitted, since I ran through the autoencoder images that I didn't use for training, and it did a really good job. Does this discard overfitting? What would be your choise about the method of loss calculation and choise of optimizer? I really learned a lot thanks to this video. It pushed me to learn something new.

People saying there is no average person... The fader chooses between 2 features, in the exact middle means no feature has been chosen. there is no person if no feature is chosen, like in a drop down menu you have to choose something.

It would be really nice to see this done with perhaps a much larger data set but maybe with 100 parameters, then hide all but about 20-30 of the less important parameters and have all of the others being randomly shifted constantly to see if it makes any kind of aesthetic. However, it would be amazing if there was some kind of download link to play around with this ourselves. I hope one becomes available sometime!

Six years ago? Wow! And it is still online? Wow times Wow!

I feel like the complications were just due to taking a shortcut you assumed would work, but didn't. And I suspect you'd get better results by simplifying your algorithm to actually encode first rather than use two out-of-the-box dimensionality reduction algorithms before finally applying the dimensionality reduction algorithm that this video is actually about.

Wow, in the latent space representation, the activations are correlated. Who knew? Not me. Please keep doing this.

8:38 OH GOD OH GOD hey, that one is pretty OH GOD

I mean people and others have been doing this for thousands of years so why is this so impressive?

Imagine being a hypercube with all the generated faces

You’ve created some good Nightmare fuel there.

0:14 is that ksi

I absolutely loved this video. Thank you. I only just found your channel today for the first time, I’m now binging all of your videos! Love you dude!

cool tech.. but don't get me wrong.. every picture says: PLEASE KILL MEEEEEEE!

I am studying media technology and this is really a nice way to explain everything.

2024 could you have predicted Ai to be what it is now?

Totally awesome video! Based on your insights, you could preprocess images to make largely redundant some of the biggest PCA components. Eg alighn all faces to the centre of the image, adjust for size differences of the face and maybe rotate faces so to be not tilted. Maybe also add 2 faces to the dataset which you generate yourself by averaging the faces of all girls and all guys. Those are likely to be used as major parts of the PCA axis for gender. Then rerun the training process. With a bit of iterative tweaking like that, my goodness, you really could have an amazing tool for modeling faces with all sorts of real world commercial applications. Well done mate! Brilliant work.

6:37 Wouldn’t you like to know, weatherboy!

The statistical analysis by the author was really interesting.

This is more horrifying than "this person does not exist" so congrats.

I know nothing of coding, but found this thoroughly entertaining. You're extremely promising.

So gender is on a spectrum? Woah...

I for one definitely enjoy the more technical videos, keep up the good work!

Somewhere among the 80 parameters there must be the Francis Bacon portrait effect

Then imagine 1,000 or 100,000 points where the computer can detect changes in the same face, by fractions of a millimeter and can calculate the predicted aging of a person or, mood, energy, awareness and so on. Maybe even signs of illness or preventing stress.

2:35 "We dont actually need the encoder. NOT EVEN DURING TRAINING. Instead we just embed all training sample randomly into the latent space. Their weights then just get updated just like the network weight during training" I got a bit lost there. How do you get those training sample? Where do you get those samples from the pictures if you don't encode them first?

The idea to use this for identifying criminals by victims is absolutely brilliant!!! Firstly, you can have them all posed uniformly for much better NN learning, since, duh, arrested. And secondly, the samples would all be registered criminals. Just imagining how this would increase efficiency of police sketching makes me shiver!

You should do this with bob ross paintings (there are 403 total)

I understand very little about math and complicated scientific whatever. But I'm still interested and I love listening to people talk about this stuff.

Those faces are some real nightmare fuel jesus

One feature that you may wish to try encoding is the fact that faces are approximately symmetrical around an axis that will be approximately vertical. I found it interesting that there was quite a lot of asymmetry in many of the images, though perhaps this is a prejudice that my brain applies based on being fairly good at recognizing faces.

Very interesting, you would have gotten better results had you normlized the face sizes and cut out the faces discarding the shirt and hair all together, thus ignoring insignificant traits such as shirt color and colar length and focusing on more interesting traits such as eyes shape, nose shape etc'.

now we can just “hey chatgpt can you write a 50 page essay about hot dogs for me” “yeah sure”

Is there some way I can play with the sliders?

I had absolutely no idea what you were speaking about, but i still found this very interesting lol.

8:55 sleep paralysis demon

i recalled and wanted to watch that video again after years, for some reasons in my memory the faces would look almost perfect except low res haha.

"Number 8" at 6:52 seems like it's skin color with darker skin on top and lighter skin on the bottom.

Your friend: Don't worry, nobody ever looks at yearbook photos You in the yearbook, making it into a video with a million views

it COULD be used to make police sketches... ORRR it could go the other way and be used to make fake ID's

3:15 i would kill to have a horror game with these faces in it it’s so unsettling and i think it’ll make for an amazing scare