FaceNet
A 2015 Google model that revolutionised facial recognition via embeddings.
📖 Full definition
FaceNet, introduced by Google in 2015, was the first model to learn a facial embedding directly optimised for similarity (rather than classification). It reached 99.6% accuracy on the LFW benchmark. Its principle — "triplet loss" — is still used today.
💡 Concrete example
Google Photos uses FaceNet to automatically group photos of the same person in your library.
🔗 See also
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