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· 2015

FaceNet: A unified embedding for face recognition and clustering

Florian Schroff, Dmitry Kalenichenko, James Philbin

Short summary

FaceNet learns a direct mapping from face images to a compact 128-byte embedding space, achieving state-of-the-art face recognition accuracy of 99.63% on LFW and 95.12% on YouTube Faces DB, cutting error rates by 30% compared to prior best results.

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Field: Computer Vision and Pattern Recognition

Computer Vision and Pattern RecognitionComputer Science