Dear Fellow Scholars, this is Two Minute Papers with Dr. Károly Zsolnai-Fehér.
Today, we are able to take a bunch of photos, and use an AI to magically, create a video
where we can fly through these photos. It is really crazy, because this is possible today,
for instance, here is NVIDIAs method that can be trained to perform this in a matter of seconds.
Now, I said that in these we can fly through these photos. But here is an insane idea:
what if we used not multiple photos, but just one photo, and we don’t fly through it, but fly
into this photo. Now, you are probably asking, Károly, what are you talking about? This
is completely insane, and it wouldn’t work with these NERF-based solutions like the one you see
here, these were not designed to do this at all! Look. Oh yes. That.
So, in order to fly into these photos, we would to invent at least 3 things. One,
image inpainting. Look, if we are to fly into this photo, we will have to be able to look at
regions between the trees. Unfortunately, these are not part of the original photo, and hence,
new content needs to be generated intelligently. That is a formidable task for an AI,
and luckily, image inpainting techniques already exist out there. Here’s one.
But inpainting is not nearly enough. Two. As we fly into a photo,
completely new regions should also appear that are beyond the image. This
means that we also need to perform image outpainting, creating these new regions.
Continuing the image, if you will. Luckily, we are entering the age of AI-driven image generation,
and this is also possible today, for instance, with this incredible tool.
But even that is not enough. Why is that? Well, three! As we fly closer to these new regions,
we will be looking at fewer and fewer pixels and from closer and closer, which means…this.
Oh my, another problem. So, we surely can’t solve this, right? Well, great news - we can! Here is
Google’s diffusion-based solution to super resolution, where the principle is simple:
have a look at this technique from last year. In goes a course image or video, and this AI-based
method is tasked with…this! Yes. This is not science fiction. This is super resolution,
where the AI starts out from noise and synthesizes crisp details onto the image.
So, this might not be such an insane idea after all! So, does the fact we can do all three of
these separately mean that this task is easy? Well, let’s see how previous techniques were able
to tackle this challenge. My guess is that this is still sinfully difficult to do. And…oh
boy. Well, I see a lot of glitches and not a lot of new, meaningful content being synthesized here.
And note these are not some ancient techniques, these are all from just two years ago.
It really seems there is not a lot of hope here. And now, hold on to your papers, and let’s see
how Google’s new AI puts all of these together, and lets us fly into this photo.
Wow, this is so much better! I love it. Clearly, not perfect, but I feel that this
is the first work where the flying into photos concept really comes into life.
And it has a bunch of really cool features too, for instance, one, it can generate even longer
videos, which means that after a few seconds, everything that we see is synthesized by the
AI. Two, it supports not only this boring linear camera motion, but these really cool, curvy camera
trajectories too. Putting these two features together, we can get these cool animations
that were not possible before this paper. Now, the flaws are clearly visible for everyone,
but this is a historic episode where we can invoke the three Laws of Papers to address them.
The First Law Of Papers says that research is a process. Do not look at where we are,
look at where we will be two more papers down the line. With this concept,
we are roughly where DALL-E 1 was about a year ago. That is an image generator AI that could
produce images of this quality. And, just one year later, DALL-E 2 arrived, which could do this! So,
just imagine what kind of videos this will be able to create just one more paper down the line.
The Second Law of Papers says that everything is connected.
This AI technique is able to learn image inpainting, image outpainting,
and super resolution techniques at the same time, and even combine them creatively. We don’t need
3 separate AIs to do these, just one technique. That is very impressive.
And finally, the Third Law Of Papers says that a bad researcher fails 100% of the time,
while a good one only fails 99% of the time. Hence, what you see here is always just 1%
of the work that was done. Why is that? Well, for instance, this is a neural network-based solution,
which means that we need a ton of training data for these AIs to learn on. And hence, scientists
at Google also needed to create a technique to gather a ton of drone videos on the internet
and create a clean dataset also with labelings as well. The labels are essentially depth information
which shows how far different parts of the image are from the camera. And they did it for more
than 2 million images in total. So, once again, if you include all the versions of this idea
that didn’t work, what you see here is just 1% of the work that was done.
And now, we can not only fly through photos, but also fly into photos. What a time to be alive!
What do you think? Does this get your mind going? What would you use this for?
Let me know in the comments below!
Thanks for watching and for your generous support, and I'll see you next time!