馃攳
Google鈥檚 New AI Puts Video Calls On Steroids! 馃挭 - YouTube
Channel: Two Minute Papers
[0]
Dear Fellow Scholars, this is Two Minute Papers
with Dr. K谩roly Zsolnai-Feh茅r.
[3]
With the increased popularity of online meetings,
telepresence applications are on the rise
[10]
where we can talk to each other from afar.
[13]
Today, let鈥檚 see how these powerful, new
neural network-based learning methods can
[19]
be applied to them.
[20]
It turns out, they can help us do everyone鈥檚
favorite, which is, showing up to a meeting,
[27]
and changing our background to pretend we
are somewhere else.
[31]
Now that is a deceptively difficult problem.
[34]
Here, the background has been changed, that
is the easier problem, but, look!
[40]
The lighting of the new environment hasn鈥檛
been applied to the subject.
[45]
And now, hold on to your papers, and check
this out.
[49]
This is the result of the new technique after
it recreates the image as if she was really
[55]
there.
[56]
I particularly like the fact that the result
includes high-quality specular highlights
[61]
too, or in other words, the environment reflecting
off of our skin.
[66]
However, of course, this is not the first
method attempting this.
[71]
So let鈥檚 see how it performs compared to
the competition!
[75]
These techniques are from one and two years
ago, and鈥hey don鈥檛 perform so well.
[82]
Not only did they lose a lot of detail all
across the image, but, the specular highlights
[88]
are gone.
[89]
As a result, the image feels more like a video
game character than a real person.
[95]
Luckily, the authors also have access to the
reference information to make our job of comparing
[100]
the results easier.
[103]
Roughly speaking, the more the outputs look
like this, the better.
[107]
So now, hold on to your papers, and let鈥檚
see how the new method performed.
[112]
Oh yes!
[114]
Now we鈥檙e talking!
[116]
Now, of course, not even this is perfect.
[119]
Clearly, the specularity of clothing was determined
incorrectly, and the matting around the thinner
[126]
parts of the hair could be better, which is
notoriously difficult to get right.
[131]
But, this is such a huge step forward in just
one paper.
[136]
And we are not nearly done - there are two
more things that I found to be remarkable
[141]
about this work.
[142]
One, is that the whole method was trained
on still images, yet, it still works on video
[149]
too!
[150]
And we don鈥檛 have any apparent temporal
coherence issues, or in other words, no flickering
[156]
arises from the fact that it processes the
video as not a video, but a series of separate
[162]
images.
[163]
Very cool.
[165]
Two, if we are in a meeting with someone and
we like their background, we can simply borrow
[171]
it.
[172]
Look.
[173]
This technique can take their image, get the
background out, estimate its lighting, and
[179]
give the whole package to us too.
[181]
I think this will be a game changer.
[184]
People may start to become more selective
with these backgrounds, not just because of
[188]
how the background looks, but, because how
it makes them look.
[193]
Remember, lighting off of a well chosen background
makes a great deal of a difference in our
[198]
appearance in the real world, and now, with
this method in virtual worlds too.
[204]
And this will likely happen not decades from
now, but in the near future.
[210]
So this new method is clearly capable of some
serious magic.
[214]
But how?
[216]
What is going on under the hood to achieve
this?
[219]
This method performs two important steps to
accomplish this, step number one is matting.
[225]
This means separating the foreground from
the background, and then, if done well, we
[230]
can now easily cut out the background and
also have the subject on a separate layer
[236]
and proceed to step number two.
[239]
Which is, relighting.
[241]
In this step, the goal is to estimate the
illumination of the new scene and recolor
[246]
the subject as if she were really there.
[250]
This new technique performs both, but most
of the contributions lie in this step.
[255]
To be able to accomplish this, we have to
be able to estimate the material properties
[260]
of the subject.
[262]
The technique has to know one, where the diffuse
parts are, these are the parts that don鈥檛
[268]
change too much as the lighting changes, and
two, where the specular parts are, in other
[274]
words, shiny regions that reflect back the
environment more clearly.
[279]
Putting it all together, we get really high-quality
relighting for ourselves, and given that this
[285]
was developed by Google, I expect that this
will supercharge our meetings quite soon.
[291]
And just imagine what we will have two more
papers down the line.
[295]
My goodness, what a time
[338]
to be alive!
[344]
Thanks
for watching and for your generous support,
[353]
and I'll see you next time!
Most Recent Videos:
You can go back to the homepage right here: Homepage





