How de-aging in movies got so good
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Downloadlet's take a trip back to 2006 Ian
McKellen is 67 years old Patrick Stewart
66 Hugh Jackman 38 but that's not really
relevant because in X-Men the Last Stand
these two guys don't quite look their
age their characters were digitally
deaged in what is widely known to be the
first implementation of this kind of
Technology the effect
is well I mean you know it looks like
the first time they were using this
technology but since then there have
been many attempts to level up this
illusion with varying degrees of success
because even at the highest levels of
Hollywood it is really hard to pull off
if you look at a person and there's
something not quite right with her face
what our lizard brain is telling us is
ooh that person is sick I better stay
away because I don't want to get sick
that's Kevin Bailey I'm the visual
effect supervisor on here he was one of
the people tasked with making sure the
film making team could pull off an
ambitious 53 minutes of daging work for
Tom Hanks Robin Wright Paul betney and
Kelly Riley or perhaps we should say
reaging as these extremely famous faces
become much younger and much older than
they are right now people that are
critical of daging and face replacement
they have every right to be we have it
all worked out we have it all worked out
it's a very very hard effect to pull off
because we just we look at human faces
all day every day it's the thing that we
recognize the most but Kevin and
Hollywood have a new film making toolkit
one that makes convincingly changing an
actor's age much more
achievable daging actors is a
painstaking process often times we'll 3D
scan an actor and build a full
three-dimensional version of their head
in the computer then from there you have
to like build every muscle and how the
skin moves when each muscle is activated
and how the blood flows in and out of
the skin as it moves and where the peach
fuzz lies trying to recreate reality
from the inside out in that approach and
it can yield really impressive results
the problem is it is so labor intensive
it's like giving birth and since all
this meticulous face spping takes place
after filming is wrapped there's a huge
amount of subjectivity and kind of
filtering in between what the actor does
and what ends up on the screen which is
one of the reasons they felt that a face
swap and post wasn't going to cut it for
here it was clear that traditional means
of de-aging was was never going to work
at the quantity that we had to address
and certainly not at the Quality
consistently throughout the production
that we needed and it wasn't until we
saw the results of the very first test
by uh this company metaphysic that we
kind of went ah gosh than thank you know
we we can do this metaphysic enabled
Elvis to perform on America's Got Talent
and also made the backup singers look
exactly like the judges it's kind of
freaky they helped Eminem dance with his
young younger self and brought Ian home
back from the dead they're an AI company
that's been making waves in Hollywood
during a time where there's still some
uncertainty and discomfort over the
technology they use sophisticated
machine learning to generate faces but
maybe it's better to let Kevin explain
we want Tom to be 20 and then 25 and
then 30 and then 35 so we kind of create
these groupings of images that we can
feed the AI with and teach it um in the
same way that if I gave you a book uh
that thick you know thousand pages of
images of Tom Hanks from all different
kinds of places they might be family
photos they might be publicity still
movie posters images from films he's
been in and I said all right Ed you're
going to do nothing for the whole week
but flip through the pages of that book
and just study Tom hanks's face to study
his likeness if at the end of that week
as long as you're a visual person if I
said to you okay now close your eyes and
imagine Tom Hanks singing happy birthday
to you in the Moonlight
even though none of those images had
shown that you would still be able to do
that very clearly in your head people
confuse it for like you know you feed a
10,000 images and it finds the closest
one and it kind of collages it onto a
person's face it's actually it's not
using a single Pixel from any of the
data that it's trained on so it's more
like it's drawing an entirely new face
with every frame as opposed to copying
and pasting pieces of other photos onto
the same face to assemble a new one you
won't find two faces that are alike in
in any of the training material and what
ended up in the movie this is what
machine learning is good at absorbing a
bunch of data in this case people's
faces and generating something new but
the particularly groundbreaking aspect
of this implementation was the speed at
which you could work which changed the
production entirely it's like really
fast like it it will do its thing in
like you know milliseconds that is what
we use to do the live on set face swaps
we would have one monitor that had young
Tom Hanks on it and one that had him at
current day and that was really powerful
it allowed for immediate onset course
Corrections by the actors themselves
because every time after Boba is called
cut they would look and kind of go like
yeah you know I'm I'm Shuffling a little
bit here maybe I you need to stand up
more straight to sell the sort of like
physicality illusion or ooh I was
overacting my youth in that take let's
di that back a bit let's do another take
and so it really brought the actor into
the conversation and allowed them to use
it as a tool it also helped them sear
away from a situation where an actor has
been made to look young but their
physicality doesn't feel young like
dair's character here in the Irishman
he's supposed to be a rugged and tough
mobster here and I mean he just looks
like my grandfather trying to kick
someone while they're down shout out to
this guy for selling it though no I'm
not a AF and I mean mean no disrespect
to the absolute Powerhouse of an actor
that Robert DeNiro is obviously this
kind of thing just couldn't be addressed
because the daging was happening solely
at the end of the pipeline it's very
easy to look at a
67-year-old acting young and think God
they look so young but then if you were
to put a 20-year-old face on them they
would look like they were a
20-year-old's face on a 40-year-old body
right and it's just like very lizard
brain reaction it's something deep
inside of us that tells us that
something isn't quite right if you look
Clos ly you can see that the real time
daging works on the face but it leaves
the ears and the neck untouched that
didn't really matter because the other
benefits of the realtime feed was that
the editors could use the Half Baked
footage to assemble early drafts of the
film so it was incredible walking away
from set with like every shot that was
going to be a face swap shot there was
already a very rudimentary version but
pretty convincing version of it already
done it was just just a little soft and
then in post- production we used very
similar AI tools but much much higher
Fidelity so instead of doing you know a
face swap in 10 milliseconds it'll take
a few minutes but that way we can get
like the real film quality High Fidelity
results out of it when it comes to
making people older I had to ask Kevin
about this scene because I found it so
moving and the performances are so good
especially uh Paul betney Rose she she
loved having you all around her she
loved this day she loved she loved
cooking for you she live for you you
should for you dad I was like oh my God
it just I really felt it and I I imagine
that's one of the scenes where you guys
Key Vocabulary (50)
toward
"Go to school."
belonging
"Cup of tea."
also
"You and me."
inside
"In the house."
specific
"That book."
A third-person singular pronoun used to refer to an object, animal, or situation that has already been mentioned or is clear from context. It is also frequently used as a dummy subject to talk about time, weather, or distance.
Used to show who is intended to have or use something, or to explain the purpose or reason for an action. It is also frequently used to indicate a specific duration of time.
A preposition used to indicate that something is in a position above and supported by a surface. It is also used to indicate a specific day or date, or to show that a device is functioning.
A preposition used to indicate that people or things are together, in the same place, or performing an action together. It can also describe the instrument used to perform an action or a characteristic that someone or something has.
Used to refer to the person or people that the speaker is addressing. It is the second-person pronoun used for both singular and plural subjects and objects.
A preposition used to indicate a specific point, location, or position in space. It is also used to specify a particular point in time or a certain state or activity.
Used to identify a specific person, thing, or idea that is physically close to the speaker or has just been mentioned. It can also refer to the present time or a situation that is currently happening.
A coordinating conjunction used to connect two statements that contrast with each other. It is used to introduce an added statement that is different from what has already been mentioned.
Used to indicate the starting point, source, or origin of something. It can describe a physical location, a point in time, or the person who sent or gave an item.
A third-person plural pronoun used to refer to two or more people, animals, or things previously mentioned. It is also commonly used as a singular pronoun to refer to a person whose gender is unknown or to someone who identifies as non-binary.
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This tool might just change movies forever. Subscribe to our channel! http://goo.gl/0bsAjO In 2025, Tom Hanks is 67 years old. Yet, in his latest film Here (directed by Robert Zemeckis),...
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