
Colorful Image Colorization - stared
http://richzhang.github.io/colorization/
======
saurik
[http://richzhang.github.io/colorization/resources/imagenet_c...](http://richzhang.github.io/colorization/resources/imagenet_comparison.html)

This is amazing. Looking at the example comparison list, I love seeing the
algorithm "correct" the color based on its biases. "No, people do not have
pink hair: I made you blond." "Shoes are always a shade of brown (including
black); the idea of shoes that are pink, purple, or even grey, morally offends
me." "I don't understand why you would paint the frame of this window that
crazy shade of green... let's go with a dark stain; doesn't that look
classier?" "I've seen this insect before: I don't remember its name, but it
was definitely brown, so stop trying to trick me into thinking it is bright
blue with your silly Photoshop shenanigans." "Also: I've seen muzzles before,
and they are made out of rusted metal; I don't know where you got this blue
rubber-coated comfort muzzle, but back in my day we didn't have those
extravagances." "On a similar note: I don't understand how your watch is
glowing blue... back lights are supposed to be a dull and mottled yellow."
"One red stripe on your truck is enough to make the point: three red stripes
makes you look like you have no taste :/." "And why would you go to the
trouble of forcing people to take a photo in front of a custom backdrop and
not take the opportunity to print the name of your company in an eye-catching
color, such as red?" "I am pretty certain all radiators everywhere are colored
using the same aging white paint that has started browining from the heat; it
gives a comfortable feeling of familiarity that your bright green radiator
lacks." "Mittens are supposed to be festive, so why did you get grey ones?!
I've colored them red: that should help."

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ilovefood
Seriously?? This is like the uber of cool or the spotify of awesome!! There's
a link in this blog
[http://tinyclouds.org/colorize/](http://tinyclouds.org/colorize/) where you
can get the trained model for Tensorflow. I'll try this out. MIND = Blown.

~~~
StavrosK
Seriously what the hell? How does it even know that the people in the Cartier-
Bresson photo are black? I have no idea how it's doing that stuff.

~~~
IanCal
It doesn't really need to, it just needs to expect it to be skin.

I'll probably get some terms wrong here as it's been a little while since I
did this kind of thing but:

When you look at skin, people seem to have very different colourings. I've got
freckles so I'm even patchy, and depending on the time of year will be lighter
or darker. However, skin colour when you remove _brightness_ becomes much more
standard. There's remarkably little variation between a normalised colour of
black and white skin, black skin is simply darker.

Look at the water by the faces, it's quite a generically caucasian colour.
That's because it's just _lighter_.

Here's some old stuff I did with finger pointing detection:
[https://figshare.com/articles/Finger_pointing_detection/9531...](https://figshare.com/articles/Finger_pointing_detection/953171)

[https://ndownloader.figshare.com/files/3155228](https://ndownloader.figshare.com/files/3155228)
<\- A plot of measured skin colours

[https://ndownloader.figshare.com/files/3155291](https://ndownloader.figshare.com/files/3155291)

~~~
simcop2387
That makes a lot of sense given that skin is colored by melanin. I would
expect some small differences due to the fact that lighter skin colors are a
bit more transparent but that they largely have the same base is pretty neat.

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oceanofsolaris
This is rather impressive. Similarly to the cited work
[http://tinyclouds.org/colorize/](http://tinyclouds.org/colorize/), it does
however seem to have a slight bias towards brownish colors (giving many images
a sepia look).

One thing very noticeable in both works is also the tendency to overshoot
borders when coloring. In many images it can be seen that the color of the
main subject bleeds into the background. A good example is e.g. the fifth
picture in
[http://richzhang.github.io/colorization/resources/images/exs...](http://richzhang.github.io/colorization/resources/images/exs_sel_aa.jpg)
, where parts of the sky get assigned the same color as the mesa. This looks
like something that should be fixable if one tries to detect these kind of
edges and gives less weight to information from the other side of such an
edge.

Does anyone know what the differences between this and the previous neural net
approach are on a technical level?

~~~
neckro23
The Ansel Adams examples are interesting because AA very deliberately
manipulated the relative intensity of tones in his photographs.

In fact, I'm not sure how applicable the current training method (desaturate a
color photo, colorize it, compare it to the original) is to actual B&W
photographs. Black-and-white photography is not a simple matter of
desaturation.

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sarreph
My first thought was "I hope this is someone showing off their photo-editing
skills because if an algorithm did this then my mind is fully blown"...

Either this or it's an advanced April Fool's release (with back-dating and
references)!

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tyingq
It's impressive, but they do mention that the examples on the front page are
where it did well.

You can see some of the other results, including many there didn't work well
at all, here:
[http://richzhang.github.io/colorization/resources/imagenet_c...](http://richzhang.github.io/colorization/resources/imagenet_comparison.html)

~~~
web007
They have the "best" and "worst" matches at the bottom of the page. I thought
the "worst" set was pretty good, and I wonder if correcting for white balance
would have given them a HUGE benefit. The majority of the errors look like
daylight-for-tungsten correction, just tweak the yellows to blues FTW.

~~~
tyingq
It seems to guess red at odd times, like
[http://richzhang.github.io/colorization/resources/images/ima...](http://richzhang.github.io/colorization/resources/images/imagenet_comparison//ours/9839.jpg)

Is that white balance related?

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hashmymustache
Very impressive. Is it possible to combine this with a semantic analyzer in
some way? Seems like having a first pass through one and then serving that
output on top of raw image pixels could reduce the potential color space and
maybe blunt training set biases? To wit, I know nothing about these things.

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ickwabe
This is very impressive but I'll be that person.

I shudder when I see someone/something colorize the works of masters of black-
and-white like Ansel Adams or Henri Cartier-Bresson. Just a horrible mangling
of their work.

Adams for example could have used color, and did take many hundreds of color
photos[1]. But in his work for display he deliberately and consciously chose
black-and-white and put in much effort in the lab to get the final images just
they way he wanted them.

So while I truly appreciate the technological achievement here, I still cringe
at the what I see as distorting the artists' work.

[1][http://www.smithsonianmag.com/arts-culture/ansel-adams-in-
co...](http://www.smithsonianmag.com/arts-culture/ansel-adams-in-
color-145315674/?no-ist)

~~~
mistercow
I really don't think the intention is to say "look we improved this!", but
rather to have a visually striking (since the original photo is visually
striking) result that doesn't have a "ground truth color" to compare it to.

~~~
ickwabe
Yes of course and I appreciate that. Just my opinion but in that case I would
not have used images with such artistic weight. There certainly plenty black
and white images to choose from.

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visarga
This technique could be applied to archive b/w photos and footage. In the same
line of ideas, it's a pity that some classical music recordings are very
distorted. Some have been recorded by famous players who are long dead and
carry important significance.

Maybe there is a way to transform noisy recordings into ones that sound as if
they were recorded in a modern studio. They could first try to emulate noise
and distortions and generate a dataset of distorted recordings, then train a
NN to reconstruct the original.

~~~
stepvhen
I, for one, would not appreciate it if entire swaths of b/w photographs were
needlessly colorized for "archiving", especially the Ansel Adams. His
photography was too good for the exact medium he chose, and colorizing them
detracts from the image.

Colorization is super cool and whatnot, but I don't think it should be applied
to art.

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cesarbs
Am I the only one confused by the title? I honestly thought it would be an
April Fool's joke :) The title makes me think it's about coloring colored
images.

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chias
This is very cool.

Aside from how impressive this is from a technical standpoint, I love that
this algorithm seems to be a little colorblind in the _human_ sense -- looking
at the military trucks and uniforms in particular, it seems to have trouble
with reds vs greens.

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dharma1
Very impressive

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vmasto
Previous HN discussion on this
[https://news.ycombinator.com/item?id=10864801](https://news.ycombinator.com/item?id=10864801)

~~~
stared
No. It is a different post, on a different research, by different people (on
the same topic).

I consider the earlier result is of much worse quality. (Saw it, but I was
hardly impressed.)

