Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Leveraging Billions of Faces to Overcome Performance Barriers in
  Unconstrained Face Recognition   We employ the face recognition technology developed in house at face.com to a
well accepted benchmark and show that without any tuning we are able to
considerably surpass state of the art results. Much of the improvement is
concentrated in the high-valued performance point of zero false positive
matches, where the obtained recall rate almost doubles the best reported result
to date. We discuss the various components and innovations of our system that
enable this significant performance gap. These components include extensive
utilization of an accurate 3D reconstructed shape model dealing with challenges
arising from pose and illumination. In addition, discriminative models based on
billions of faces are used in order to overcome aging and facial expression as
well as low light and overexposure. Finally, we identify a challenging set of
identification queries that might provide useful focus for future research.

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The categories of this paper are: nlin
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The categories of this paper are: solv-int
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The categories of this paper are: hep-lat
13
The categories of this paper are: quant-ph
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The categories of this paper are: comp-gas
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The categories of this paper are: atom-ph
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The categories of this paper are: plasm-ph
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The categories of this paper are: math
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The categories of this paper are: eess
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The categories of this paper are: hep-th
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The categories of this paper are: math-ph
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The categories of this paper are: patt-sol
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The categories of this paper are: adap-org
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The categories of this paper are: gr-qc
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The categories of this paper are: nucl-ex
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The categories of this paper are: econ