
How I implemented iPhone X’s FaceID using Deep Learning in Python - dsr12
https://towardsdatascience.com/how-i-implemented-iphone-xs-faceid-using-deep-learning-in-python-d5dbaa128e1d
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codelord
For those who are new to machine learning, this is like duct taping four
wheels together and calling it a Lamborghini. Maybe a good start if you want
to learn about basics of face recognition, but iPhoneX FaceID keywords here
are clickbait. This is nothing like the technology used in iPhoneX.

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hondadriver
Can you please explain further? How does it work on the iPhone? How is it
different from this method?

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220V_USKettle
The technique in the article does not seem to be using depth data (there is a
picture in the article), only RGB image data.

So, he could have gotten the same results with a webcam.

My understanding is that these depth cameras create a 3d point cloud and use
the rgb to map/overlay color onto the 3d.

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metafunctor
The article does mention doing experiments using depth information from a
Kinect. Also, the actual code on the github repo does appear to use depth
info.

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kccqzy
I’d love to see some comparison between this prototype and real FaceID. How
good are each at recognizing the same people with different appearances
(haircut, glasses)? How good are each at rejecting different people with
similar looks like siblings?

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thasaleni
Even apple can't tell the difference between twins

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omarforgotpwd
Crazy to think that a ton of neural networks are running on live sensor data
every time I unlock my phone. Truly amazing and seamless technology.

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ellisv
Applying the model is fast, training it is slow(er). Not that crazy.

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omarforgotpwd
For something as common as unlocking my phone, the algorithm needs to be
extremely fast and power efficient not to mention this is a PHONE, so yes I
still find this impressive. The fact that sensor data is being processed
through a neural network using a dedicated chipset for neural net operations
would seem like ridiculous overkill if you explained it to me ten years ago.
Furthermore, the network is actually being re-trained on the fly to
accommodate for changes to the users facial hair, etc.

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innagadadavida
Can someone who’s actually worked/implemented/published face
detection/recognition please point to state of the art results for this task?
Are neural networks better than hand crafted feature extractors?

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normandp
I based my work on FaceNet, a quite recent paper that achieves state-of-the-
art results and incredible robustness using very similar techniques to the
ones I implemented here (siamese networks, contrastive/triplet loss).

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sebastianmarkow
Duct tape PhD notebook. These prime examples of "Untitled.ipynb mentality" are
what makes me shake my head. No annotations, no exploration of the dataset, no
sanity checks, printf debugging, uncaught error messages. But putting just
because it doesn't collapse under your feet, put your name upfront and it's
good to go.

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nailer
Very minor nitpick: Surface devices have combined infrared and regular cameras
for face unlocking for years. It's a great tech but it didn't start with the
iPhone X.

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ggg9990
I don’t have the iPhone X but the Surface Face ID is a piece of shit.

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cube2222
Surface hello works for me nearly every single time fast and seemlessly. Love
it.

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ggg9990
Looks like it isn’t random per day but rather works well on some faces and
terribly on others.

