Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Discovering Underlying Person Structure Pattern with Relative Local
  Distance for Person Re-identification   Modeling the underlying person structure for person re-identification (re-ID)
is difficult due to diverse deformable poses, changeable camera views and
imperfect person detectors. How to exploit underlying person structure
information without extra annotations to improve the performance of person
re-ID remains largely unexplored. To address this problem, we propose a novel
Relative Local Distance (RLD) method that integrates a relative local distance
constraint into convolutional neural networks (CNNs) in an end-to-end way. It
is the first time that the relative local constraint is proposed to guide the
global feature representation learning. Specially, a relative local distance
matrix is computed by using feature maps and then regarded as a regularizer to
guide CNNs to learn a structure-aware feature representation. With the
discovered underlying person structure, the RLD method builds a bridge between
the global and local feature representation and thus improves the capacity of
feature representation for person re-ID. Furthermore, RLD also significantly
accelerates deep network training compared with conventional methods. The
experimental results show the effectiveness of RLD on the CUHK03, Market-1501,
and DukeMTMC-reID datasets. Code is available at
\url{https://github.com/Wanggcong/RLD_codes}.

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The categories of this paper are: atom-ph
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The categories of this paper are: dg-ga
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The categories of this paper are: adap-org
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The categories of this paper are: q-fin
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The categories of this paper are: cond-mat
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The categories of this paper are: chem-ph
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The categories of this paper are: nucl-ex
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The categories of this paper are: astro-ph
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The categories of this paper are: hep-lat
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The categories of this paper are: plasm-ph
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The categories of this paper are: supr-con
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The categories of this paper are: ao-sci
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The categories of this paper are: nlin
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The categories of this paper are: q-alg
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The categories of this paper are: bayes-an
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The categories of this paper are: funct-an