Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Automatically Building Face Datasets of New Domains from Weakly Labeled
  Data with Pretrained Models   Training data are critical in face recognition systems. However, labeling a
large scale face data for a particular domain is very tedious. In this paper,
we propose a method to automatically and incrementally construct datasets from
massive weakly labeled data of the target domain which are readily available on
the Internet under the help of a pretrained face model. More specifically,
given a large scale weakly labeled dataset in which each face image is
associated with a label, i.e. the name of an identity, we create a graph for
each identity with edges linking matched faces verified by the existing model
under a tight threshold. Then we use the maximal subgraph as the cleaned data
for that identity. With the cleaned dataset, we update the existing face model
and use the new model to filter the original dataset to get a larger cleaned
dataset. We collect a large weakly labeled dataset containing 530,560 Asian
face images of 7,962 identities from the Internet, which will be published for
the study of face recognition. By running the filtering process, we obtain a
cleaned datasets (99.7+% purity) of size 223,767 (recall 70.9%). On our testing
dataset of Asian faces, the model trained by the cleaned dataset achieves
recognition rate 93.1%, which obviously outperforms the model trained by the
public dataset CASIA whose recognition rate is 85.9%.

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The categories of this paper are: funct-an
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The categories of this paper are: quant-ph
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The categories of this paper are: acc-phys
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The categories of this paper are: hep-lat
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The categories of this paper are: hep-th
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The categories of this paper are: hep-ex
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The categories of this paper are: comp-gas
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The categories of this paper are: ao-sci
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The categories of this paper are: adap-org
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The categories of this paper are: dg-ga
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The categories of this paper are: mtrl-th
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The categories of this paper are: physics
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The categories of this paper are: math-ph
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The categories of this paper are: eess
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The categories of this paper are: nucl-th
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The categories of this paper are: chem-ph