deep learning reveals the essence of matt damon

DEEP LEARNING REVEALS THE ESSENCE OF MATT DAMON

MY FACE IS NOT THAT DIFFERENT FROM A MOVIE STAR’S AND DAMN IT I’M GONNA PROVE IT USING DEEP LEARNING.

DiscrimInatorGENERATOR

GENERATIVE ADVERSARIAL NETWORKS

GENERATOR

[ ]-0.2 0.4 -0.9 0.7

GENERATOR

[ ]0.1 0.1 -0.3 -0.4

GENERATOR

[ ]0.5 -0.4 -0.3 -0.8

FAKE

DiscrimInator

REAL

DiscrimInator

FAKE

DiscrimInator


AN ARMS RACE


Here, try this…


This is fake!

FAKE


Yay I’m right!

FAKE


Damn, how is he figuring it out? Oh, it needs to be roundish and orange. Here, try this!


I think this is real.

REAL


Dang! I’m wrong. How is he fooling me? Aaah, I should check for well defined eyes.

REAL


We are doing well. Try this!


I think this is fake.

FAKE


Yay! I’m right.

FAKE


Damn, how is he figuring it out? Oh, the eyes need to be well defined. Here, try this!


Man, I am getting super awesome.


HOW DO THEIR INNARDS WORK?

25

THIS CHEEKY BASTARDIS TRYING TO TRICK YOU

28

FAKE

H

FAKE

Y

FAKE

C

X

O

FAKE

29

FAKE

REAL

FAKE

REAL

FAKE

REAL

REAL

REAL

FAKE

CLASSIFICATION30

DiscrimInator

CLASSIFICATION31

REAL

REAL

REAL

REAL

REAL

FAKE

FAKE FAKE

FAKE

DiscrimInator

TRAIN

CLASSIFICATION32

REAL

REAL

REAL

REAL

REAL

FAKE

FAKE FAKE

FAKE TRAIN

DiscrimInator

CLASSIFICATION

DiscrimInator

CLASSIFICATION

REAL

DiscrimInator

CLASSIFICATION

FAKE

DiscrimInator

LOGISTIC REGRESSION

PROB(REAL)

Feature 1

Feature 2

Feature 3

Feature 4

Feature 5

Feature 6

Feature 7

Feature 8

Feature 9

38

0.6 1.0 0.0

0.0 0.2 0.4

0.7 1.0 0.8

0.7 0.8 0.7

0.8 0.0 0.8

0.7 0.8 0.7

0.8 0.0 0.8

0.8 0.7 0.8

0.8 0.0 0.8

0.9 0.0 0.8

0.2 1.0 0.2

0.0 1.0 0.0

0.9 0.9 0.8

1.0 0.1 0.0

0.9 0.9 0.8

0.2 0.2 0.4

0.2 0.3 0.0

0.6 0.2 0.6

0.7 0.0 0.8

0.9 0.8 0.1

0.7 0.0 0.0

0.7 0.4 1.0

0.0 0.1 1.0

0.0 0.3 0.1

0.9 0.1 0.9

0.1 0.7 0.1

0.9 0.1 0.9

0.8

0.8 0.0 0.8

0.8 0.7 0.8

0.8 0.0 0.8

0.7 0.4 1.0

0.0 0.1 1.0

0.0 0.3 0.1 0.3

CAN’T CATCH COMPLEX LOCAL & NONLINEAR RELATIONSHIPS

DEEP LEARNING

0.7 0.0 0.8

0.9 0.8 0.1

0.7 0.0 0.8p(R)

HIDDENFEATURES

(1)

HIDDENFEATURES

(2)

CONVOLUTIONAL NEURAL NETWORK

0.7 0.0 0.8

0.9 0.8 0.1

0.7 0.0 0.8p(R)

Rectified Linear Units and Batch Normalization

0.7 0.0 0.8

0.9 0.8 0.1

0.7 0.0 0.8p(R)

p(REAL)

DiscrimInator

GENERATOR

[ ]-0.2 0.7

GENERATOR

[ ]0.9 -0.5

GENERATOR

[ ]0.1 0.3


GENERATIVE ADVERSARIAL NETWORKS

GENERATOR

IN THE END, A GOOD IMAGE GENERATOR

GENERATOR

IN THE END, A GOOD IMAGE GENERATOR

ALSO THE VECTORS CORRESPONDING TO THE IMAGES ARE IN A LINEAR SPACE. FACES WITH CLOSE VECTORS LOOK SIMILAR.

HOW WOULD A GENERATOR THINK OF MY FACE AS A VECTOR OF 100 NUMBERS?

IF I CAN CONVERT REAL FACES TO VECTORS IN LINEAR SPACE, I CAN MEASURE DISTANCES, MORPH THEM, ETC…

GENERATOR

[ ]0.5 -0.4 -0.3 -0.8

GENERATOR

?

GENERATOR

[ ]0.2 -0.3 -0.2 -0.9

START WITH A RANDOM Z, RUN OPTIMIZATION TO FIND THE Z THAT MINIMIZES A LOSS

LOSS = Pixel Differences + λ Prob(fake)

[ ]0.2 -0.3 -0.2 -0.9 [ ]0.3

-0.5 -0.4 -0.8

[ ]0.2 -0.3 -0.2 -0.9 [ ]0.3

-0.5 -0.4 -0.8

Interpolate and show corresponding images to convince everyone that it only takes very few

visual changes for my face to become Matt Damon’s

AND FINALLY

[ ]x x x x [ ]x

x x x [ ]x

x x x [ ]x

x x x [ ]x

x x x [ ]x

x x x [ ]x

x x x [ ]x

x x x

THE ESSENCE OF IRMAK

[ ]x x x x


THE PLATONIC MATT DAMON


THE PLATONIC MATT DAMON

EIGEN-CLOONEY

deep learning reveals the essence of matt damon

Data & Analytics