DeepFace is a deep learning facial recognition system created by a research group at Facebook.
[1][2] The Facebook Research team has stated that the DeepFace method reaches an accuracy of 97.35% ± 0.25% on Labeled Faces in the Wild (LFW) data set where human beings have 97.53%.
As a result of growing societal concerns Meta announced[4] that it plans to shut down Facebook facial recognition system, deleting the face scan data of more than one billion users.
The company has also not ruled out incorporating facial recognition technology into future products, according to Meta spokesperson.
[5] DeepFace was produced by a collection of scientists from Facebook's artificial intelligence research team.
The team includes Yainiv Taigman and a Facebook research scientist Ming Yang.
[6] DeepFace, according to the director of Facebook's artificial intelligence research, is not intended to invade individual privacy.
Additionally, Facebook will remove images from facial recognition templates if someone has deleted their account or untagged themself from a photo.
Because of this, some individuals argue that Facebook's facial ID database could be distributed to government agencies.
In response to privacy concerns, Facebook removed their automatic facial recognition feature – allowing individuals to opt in to tagging through DeepFace.
DeepFace uses fiducial point detectors based on existing databases to direct the alignment of faces.
Because full perspective projections are not modeled, the fitted camera is only an approximation of the individual's actual face.
In the 2014 paper,[13] an additional fully connected layer is added at the end to classify the face image into one of 4030 possible persons that the network had seen during training time.
Neeraj Kumar, a researcher at the University of Washington said that Facebook's DeepFace shows how large sets of outside data can result in a "higher capacity" model.
[16] According to Broadcasting & Cable, both Facebook and Google had been invited by the Center for Digital Democracy to attend a 2014 National Telecommunications and Information Administration "stakeholder meeting" to help develop a consumer privacy Bill of Rights, but they both declined.
Broadcasting & Cable also noted that Facebook had not released any press announcements concerning DeepFace, although their research paper had been published earlier in the month.
[17][18] The technology's nearly perfect accuracy allows social media companies to create digital profiles of millions of Americans.
[19] However, an individual's fear of facial recognition and other privacy concerns does not correspond to a decrease in social media use.
The lawsuit raised against DeepFace alleges that Facebook's collection of facial identification information for the purpose of the tag suggestion tool violates BIPA.
Facebook removed their automatic facial recognition tagging feature in 2019, in response to the concerns raised in the lawsuit.
[37] Because algorithms are primarily trained with white men, systems like DeepFace have a more difficult time identifying them.
[38] It is projected that once facial recognition data bases are trained to identify people of color — exposing them to more diverse faces — they will be more successful at identification.