NVIDIA's New AI: Enhance! 🔍
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NVIDIA's New AI: Enhance! 🔍

Two Minute Papers 27.03.2022 208 839 просмотров 10 515 лайков

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Intro

Dear Fellow Scholars, this is Two Minute  Papers with Dr. Károly Zsolnai-Fehér. Today we are going to see how NVIDIA’s new  AI can do 3 seemingly impossible things   with just one elegant technique.

Nerve Based Technique

For reference, here is a previous method that  can take a collection of photos like these,   and magically, create a video where we can fly  through these photos. This is what we call a   NERF-based technique, and these are truly amazing.   Essentially, photos go in, and reality comes out. So, I know you are thinking, Károly, this looks  like science fiction. Can even this be topped?    And the answer is yes. Yes it can! Now, you see, this new technique can also   look at a small collection of photos, and, be  it people or cats, and it learns to create a   continuous video of them. These look  fantastic. And remember, most of the   information that you see here is synthetic.   Which means, it is created by the AI. So good! But, wait, hold on to your papers,   because there is a twist! It is often the  case for some techniques that they think   in terms of photos. While other techniques  think in terms of volumes. And get this,

Hybrid Technique

this is a hybrid technique that thinks in terms of  both! Okay…so what does that mean? It means this!    Yes, it also learned to now only generate these  photos, but also, the 3D geometry of these models   at the same time. And this quality for the results  is truly something else. Look at how previous

Previous Techniques

techniques struggle with the same task. Wow. They  are completely different than the input model.    And you might think that of course they are not  so good. They are probably very old methods. Well,   not quite! Look, these are not some ancient  techniques, for instance, GIRAFFE is from   the end of 2020 to the end of 2021 depending  on which variant they used. And, let’s see   what the new method does on the same data…wow. My  goodness. Now that is something. Such improvement   in so little time. The pace of progress in  AI research is nothing short of amazing. And not only that, but everything it produces is  multi-view consistent. This means that we don’t   see a significant amount of flickering as we  rotate these models. There is a tiny bit on the

Usability

fur of the cats, but other than that, very little.   That is a super important usability feature. But wait, it does even more. Two, it can also  perform one of our favorites, super resolution.

Super Resolution

What is super resolution? Simple, a coarse,  pixelated image goes in, and what comes out?    Of course, a beautiful, detailed image. And here comes number three. It projects these  images into a latent space. What does that mean?

Latent Space

A latent space is a made-up place  where we are trying to organize data   in a way that similar things are close  to each other. In our earlier work,   we were looking to generate hundreds of variants  of a material model to populate this scene. In   this latent space, we can concoct all of  these really cool digital material models.    A link to this work is available  in the video description.

Human Faces

Now, let's see. Yes. When we take a walk in  the internal latent space of this technique,   we can pick a starting point, a human face,  and generate these animations as this face   morphs into other possible human faces. In short,  this can generate a variety of different people.    Very cool. I love it! Now, of course,  not even this technique is perfect, I see   some flickering around the teeth, but otherwise,

Virtual People

this will be a fantastic tool for creating virtual  people. And remember, not only photos of virtual   people, we get the 3D geometry for their  heads too. With this, we are one step closer   to democratizing the creation of virtual humans  in our virtual worlds. What a time to be alive! And, if you have been holding on to your papers  so far, now, squeeze that paper! Because get this,

Conclusion

you can do all of this in real time. And all  of these applications can be done with just one   elegant AI technique. Once again, scientists at  NVIDIA knocked it out of the park with this one.    Bravo. So, what about you? If all this can be  done in real time, what would you use this for?    I’d love to know - please let  me know in the comments below.

Outro

Thanks for watching and for your generous  support, and I'll see you next time!

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