When I put a picture of myself that had the contrast turned up my picture was rated "godlike", when I put in the original picture it was rated "hot", and when I turned down the contrast some it was rated "ok." I'm an unhealthy, almost pasty shade of white with a slightly bulbous nose and a classic fivehead.
Obviously this is just a toy and your algorithm is pretty inexact, but... you need to fix it, or at least note in giant letters that it only works for white people right now and that you're working on your algorithm to make it more universal. Because it only (kinda, sorta?) works for white people right now. If you claim something is universal in your headline then note its specificity in the fine print, you're lying. If you build an algorithm that calls most people who aren't white ugly, you need to think about the buzz-to-backlash factor of demoing it.
It's really not a good look, and you've got a week at most before you get called a "Nazi Dating App" on twitter and your potential VCs get spooked and pull out. I don't think it's intentional on your part, but literally no one cares about what your intentions are when there's an opportunity to create moral indignation clickbait. Just a friendly word of warning!
If people are not mature enough to understand that a machine learning algorithm cannot be racist, shouldn't you go educate them instead of telling people not to offend these idiots?
Secondly what makes you think that every race is equally attractive universally? Studies have people find people of their own race more attractive. If whites are more attractive (either by their training set or user base ratings) doesn't that merely reflect the composition of their user base?
Hi, I'm Rasmus and worked on the algorithms behind faces.ethz.ch. If you have any technical questions, let me know! Sorry for having some stability issues, we got much more traffic than expected and are currently working hard to fix everything!
Cool work! I'm curious regarding the training dataset. What is the distribution of faces by race/age? Also regarding the raters, what is their distribution? (Race/age/cultural background)?
It's widely known that attractiveness is heavily dependent on cultural upbringing.
Signed,
Butthurt dev whose best pic only rated an "OK".
EDIT: You also rated Yoona (a Korean pop star) as just "Nice": http://imgur.com/uJVnQ9S. I guess that makes me feel better about my "OK". I'd stay out of Korea if I were you---I hear their fans aren't very forgiving.
Could this site be used to optimize your dating profile photo (if you have one)? I'm probably "Hmmm" on most photos but possibly "Ok" or even "Nice" on a few. What does the algorithm want?
None of the images I am uploading are working. It is saying it cannot detect a face on any of them. Is this a masking of the stability error or some other issue?
I actually thought an interesting idea is an app that recommends you which dating site to use based on your face.
If you're good looking you can pretty much use whatever.
But for someone like myself who is ethnic and not visually attractive, my success rate is really low on certain sites and acceptable on certain apps.
For example, my performance on Match (Graphic I made: http://i.imgur.com/UZuSzD9.png) was pretty woeful in December. But I started using another app in the same week and had much higher success in getting responses relative to effort level.
Of course, perhaps users have trained it...particularly ones sympathetic to Carrie Fisher. Though I'd argue that they would've also corrected Boyega's face.
the flag for "Adult Content" reminds me of anecdotes about mechanical turk workers standing in to keep uploads child friendly, now mixed with Age Identification this gets a new perspective. Is this in active use somewhere?
The first processing step consist from (human) face detection. We use the standard OpenCV for our faces.ethz.ch demonstrator. A failure of this step is likely to propagate in the unreliable/wrong attractiveness prediction. For attractiveness, age, and gender prediction we start from a cropped image assumed to contain a (roughly aligned) face as found by the detector.
I hope that this helps to understand the aforementioned result.
I have a heart shaped face, a slight hawk nose, green eyes, golden hair, freckles on my cheeks, I have light skin, my forehead is an average length, my eyebrows are medium sized, and my teeth are straight
You've got to admire their honesty for not putting an image matching algorithm in to automatically say the founders are hot!
https://goo.gl/photos/jv82LHNQKxrt1Ce88
Well, it was way off on my age, but it correctly gendered me ad female. Which I find quite impressive as I am a transgender woman, I've only been on hormones for 4 months, and most humans aren't even correctly gendering in me yet.
More than anything, I'm curious to know what features it was that registered me as female. Was it as simple as the long hair, or some complicated subtle mix of many small details?
I've been on hormones for a little over two years now. Submitted several pictures from the last few months: it's consistently gendering me female (yay!) and a decade younger than I actually am (yay!), but it's saying that I'm ice cold "Hmm" (aw...).
What direction was it off on your age? I'm 31 (30 in the older pictures I sent), and it said I was 19-22 in all the pictures I tried.
This would make a great psychology experiment. Use an algorithm to detect someone's age, then randomly assign them an attractiveness score and see how their behavior differs based on the result. How does the random attractiveness result effect how likely they are to share their score? To retake the test? Does this vary based on the users age?
We thought at similar experiments, however psychology is not our expertise. If you check our paper on hotness/attractiveness (http://www.vision.ee.ethz.ch/~timofter/publications/Rothe-ar...), I am sure that you'll find some interesting results on how different age-grouped people rate, a paradox, and more. And yes, there are many interesting experiments to do and questions to answer.
As someone who switches genders I find that it guesses my trans flavor right fairly often - maybe 75% of the time. It always gets my cis flavor right.
Also, the ones it rates the least attractive it, for some reason, tends to identify me as much younger (across both genders). Like more than a decade younger than the picture, and it'll rate it "Hmm..."
As for the highest rated pictures... I can't figure out what it does; though one where someone else did my makeup and it was perfect was among the two it rated stunning. I was surprised that the ones I tried to feed it where my phone's "Beauty face" kicked in (which removes most wrinkles and skin flaws) didn't seem to rate any higher... though makeup did make a difference.
A fun little toy.
Edit: Oh, and other than occasionally docking me a decade as mentioned, it was pretty accurate on age (+-3 years, generally). Which I find interesting as I'm frequently told I look younger than I am.
31-year-old trans MTF here... uploaded my most recent picture, and it said I was 20, female, and ice cold "Hmm...".
Uploaded a picture from about a month ago... same, except it said I was 19.
Well, I'm flattered it thinks I can't drink, and I'm glad I pass. Too bad it doesn't think I'm hot, but I've always preferred to go for cute over hot anyway.
I'm gonna dig through my photos and see how consistent this is... (edit: a couple more, 21-22, female, and still ice cold)
Oh hey, I worked on something similar two years ago: http://www.FaceMyAge.com (note, the age estimator has been taken offline - because, 2 years ago).
A lot of the issues our estimator (just an age estimator) ran into were the standard face recognition problems: occlusion, lighting, and (the obvious) bogus images.
Anyone involved, what data set was the attractiveness scale built from(Labelled Faces in the Wild Dataset (http://vis-www.cs.umass.edu/lfw/))?
After 2 years we face almost the same issues, but probably we cope differently with them. Note that our solutions are fully described in the two papers mentioned on our faces.ethz.ch page. For attractiveness we used data from Blinq.
Our apparent age estimation solution is the winner of the latest LAP challenge, ICCV 2015.
It said I am 36 and I am 37. I am impressed (and Hot(tm))! However, it guessed a coworker was 34/Ummm and she is in her 50s. I am conflicted about telling her the results.
They said it themselves - "Our algorithm is trained on the pictures of the BLINQ community that is mainly based in Switzerland. In other parts of the world the perception might be very different."
A service that upvotes average to below average white people and downvotes average to above average people of color. Is someone anticipating a decline in the international value of Whiteness?
A lot of the sample photos look like they have had filters put on them. One of the things that karpathy found was that convnets were bad at images with filters.
Don't feel too bad -- I ran a photo of Brad Pitt through it and he merely got a "Nice". Granted, I tried a second one and he got "Godlike". I wonder how sensitive the results are to general lighting in the photo.
Please check our research papers linked on the webpage.
Our data consists only from normal (or natural looking) face images in the wild (from IMDB, Wiki, and/or BLINQ user profiles). On such data we get very good apparent age prediction (better than the human reference) and also very good gender and attractiveness prediction.
The attractiveness is highly subjective and its perception varies from one culture/region to another. We used data from Switzerland.
Our solutions are far from being perfect and the guessed results should not be taken too seriously.
We consider to update our models to explicitly deal with distortions and non-human face contents.
Dr_tldr|10 years ago
Now, this a problem for bigger reasons:
An older picture of Denzel Washington gets an ok: http://imgur.com/Li0gZqH
A recent picture of Howard Stern gets a hot: http://imgur.com/L8hxoVK
Obviously this is just a toy and your algorithm is pretty inexact, but... you need to fix it, or at least note in giant letters that it only works for white people right now and that you're working on your algorithm to make it more universal. Because it only (kinda, sorta?) works for white people right now. If you claim something is universal in your headline then note its specificity in the fine print, you're lying. If you build an algorithm that calls most people who aren't white ugly, you need to think about the buzz-to-backlash factor of demoing it.
It's really not a good look, and you've got a week at most before you get called a "Nazi Dating App" on twitter and your potential VCs get spooked and pull out. I don't think it's intentional on your part, but literally no one cares about what your intentions are when there's an opportunity to create moral indignation clickbait. Just a friendly word of warning!
verroq|10 years ago
Secondly what makes you think that every race is equally attractive universally? Studies have people find people of their own race more attractive. If whites are more attractive (either by their training set or user base ratings) doesn't that merely reflect the composition of their user base?
sarciszewski|10 years ago
Well, there goes my last ounce of self esteem.
If anyone needs me I'll be sitting in the corner with one of those criminal hacker ski masks while I work on open source stuff.
HSO|10 years ago
https://polybox.ethz.ch/index.php/s/tI9QTAblYVanuA9
:-)
fhars|10 years ago
minionslave|10 years ago
fatjokes|10 years ago
facepalm|10 years ago
unknown|10 years ago
[deleted]
rrothe|10 years ago
fatjokes|10 years ago
Cool work! I'm curious regarding the training dataset. What is the distribution of faces by race/age? Also regarding the raters, what is their distribution? (Race/age/cultural background)?
It's widely known that attractiveness is heavily dependent on cultural upbringing.
Signed, Butthurt dev whose best pic only rated an "OK".
EDIT: You also rated Yoona (a Korean pop star) as just "Nice": http://imgur.com/uJVnQ9S. I guess that makes me feel better about my "OK". I'd stay out of Korea if I were you---I hear their fans aren't very forgiving.
sawwit|10 years ago
bjourne|10 years ago
frik|10 years ago
MrQuincle|10 years ago
Edit: Sorry, missed it! http://arxiv.org/pdf/1510.07867v1.pdf
Madmallard|10 years ago
anotheryou|10 years ago
Picture or Extracted Face?
rubyfan|10 years ago
colmvp|10 years ago
If you're good looking you can pretty much use whatever.
But for someone like myself who is ethnic and not visually attractive, my success rate is really low on certain sites and acceptable on certain apps.
For example, my performance on Match (Graphic I made: http://i.imgur.com/UZuSzD9.png) was pretty woeful in December. But I started using another app in the same week and had much higher success in getting responses relative to effort level.
spyspy|10 years ago
dpflan|10 years ago
https://www.crunchbase.com/organization/opinionaided#/entity
http://techcrunch.com/2013/06/26/thumb-social-polling-app-me...
kevindeasis|10 years ago
kolbe|10 years ago
gepoch|10 years ago
danso|10 years ago
I mean, is it different from Project Oxford, the Microsoft API that's been around for awhile and is still quite amazing?
https://www.projectoxford.ai/demo/vision#Analysis
I actually tried it out early this morning, to compare it with a stock install of OpenCV 3. It got the faces correct, and the ages very well too.
Here are its guesses for the Star Wars TFA poster: http://imgur.com/XT7RmX6
Of course, perhaps users have trained it...particularly ones sympathetic to Carrie Fisher. Though I'd argue that they would've also corrected Boyega's face.
stephaniepier|10 years ago
Edit - tried a different pic, it guessed my fiance was 51.
drpgq|10 years ago
http://www.nist.gov/itl/iad/ig/frvt-2013.cfm
aidenn0|10 years ago
throwupper247|10 years ago
philippeback|10 years ago
m-i-l|10 years ago
- Be female.
- Face should occupy about 1/3 of the image.
- Cut off your forehead.
- Show your long hair.
- Oversaturate the face.
- Put a filter on it.
- Add a border.
dghughes|10 years ago
rootedbox|10 years ago
timofter|10 years ago
I hope that this helps to understand the aforementioned result.
unknown|10 years ago
[deleted]
cobalt|10 years ago
nogbit|10 years ago
dpflan|10 years ago
sharemywin|10 years ago
hazelhandanza|10 years ago
chrisdevereux|10 years ago
nmstoker|10 years ago
acconrad|10 years ago
thomasahle|10 years ago
glibgil|10 years ago
dholowiski|10 years ago
More than anything, I'm curious to know what features it was that registered me as female. Was it as simple as the long hair, or some complicated subtle mix of many small details?
amyjess|10 years ago
What direction was it off on your age? I'm 31 (30 in the older pictures I sent), and it said I was 19-22 in all the pictures I tried.
Houshalter|10 years ago
tomp|10 years ago
such_a_casual|10 years ago
This made me laugh really hard. What a positive twist on the fact that the algorithm is clearly a WIP.
sethbannon|10 years ago
timofter|10 years ago
I am Radu, one of the authors.
We thought at similar experiments, however psychology is not our expertise. If you check our paper on hotness/attractiveness (http://www.vision.ee.ethz.ch/~timofter/publications/Rothe-ar...), I am sure that you'll find some interesting results on how different age-grouped people rate, a paradox, and more. And yes, there are many interesting experiments to do and questions to answer.
JimboOmega|10 years ago
Also, the ones it rates the least attractive it, for some reason, tends to identify me as much younger (across both genders). Like more than a decade younger than the picture, and it'll rate it "Hmm..."
As for the highest rated pictures... I can't figure out what it does; though one where someone else did my makeup and it was perfect was among the two it rated stunning. I was surprised that the ones I tried to feed it where my phone's "Beauty face" kicked in (which removes most wrinkles and skin flaws) didn't seem to rate any higher... though makeup did make a difference.
A fun little toy.
Edit: Oh, and other than occasionally docking me a decade as mentioned, it was pretty accurate on age (+-3 years, generally). Which I find interesting as I'm frequently told I look younger than I am.
amyjess|10 years ago
Uploaded a picture from about a month ago... same, except it said I was 19.
Well, I'm flattered it thinks I can't drink, and I'm glad I pass. Too bad it doesn't think I'm hot, but I've always preferred to go for cute over hot anyway.
I'm gonna dig through my photos and see how consistent this is... (edit: a couple more, 21-22, female, and still ice cold)
asasasasasasa|10 years ago
[deleted]
Madmallard|10 years ago
http://imgur.com/Td11aoI
Yeah this site is bogus. So many inconsistent ratings.
bcook|10 years ago
Anyone tried a picture with larged amounts of cash in the background?
madaxe_again|10 years ago
amelius|10 years ago
tsumnia|10 years ago
A lot of the issues our estimator (just an age estimator) ran into were the standard face recognition problems: occlusion, lighting, and (the obvious) bogus images.
Anyone involved, what data set was the attractiveness scale built from(Labelled Faces in the Wild Dataset (http://vis-www.cs.umass.edu/lfw/))?
timofter|10 years ago
I am Radu, one of the authors.
After 2 years we face almost the same issues, but probably we cope differently with them. Note that our solutions are fully described in the two papers mentioned on our faces.ethz.ch page. For attractiveness we used data from Blinq.
Our apparent age estimation solution is the winner of the latest LAP challenge, ICCV 2015.
AnimalMuppet|10 years ago
redwards510|10 years ago
nikolay|10 years ago
- body type
- piercing
- tattoos
- eyeglasses
- colored hair
- etc.
unknown|10 years ago
[deleted]
unknown|10 years ago
[deleted]
freddealmeida|10 years ago
Check out how Sensetime did a similar feature.
nice_byte|10 years ago
tripity|10 years ago
Houshalter|10 years ago
Anyway I only got "connection error".
pmelendez|10 years ago
colmvp|10 years ago
Minus: I got the lowest rating possible. Haha, terribly depressing feedback before a date.
nilkn|10 years ago
samstave|10 years ago
Zekio|10 years ago
unknown|10 years ago
[deleted]
peter303|10 years ago
shouldbelinear|10 years ago
sawwit|10 years ago
the-13-doctor|10 years ago
thegayngler|10 years ago
tapia|10 years ago
microcolonel|10 years ago
http://pasteall.org/pic/show.php?id=97312 Off by almost a decade on age.
nnoitra|10 years ago
Check this album out: http://imgur.com/a/1a1tn
Seems racist and sexist towards men.
timofter|10 years ago
Our data consists only from normal (or natural looking) face images in the wild (from IMDB, Wiki, and/or BLINQ user profiles). On such data we get very good apparent age prediction (better than the human reference) and also very good gender and attractiveness prediction.
The attractiveness is highly subjective and its perception varies from one culture/region to another. We used data from Switzerland.
Our solutions are far from being perfect and the guessed results should not be taken too seriously.
We consider to update our models to explicitly deal with distortions and non-human face contents.
baltcode|10 years ago
totony|10 years ago
iLoch|10 years ago
Jess_the_best|10 years ago
CrowFly|10 years ago
phlandis|10 years ago
[deleted]
_asdf_asdf|10 years ago
kelvin0|10 years ago