Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Global-Local Dynamic Feature Alignment Network for Person
  Re-Identification   The misalignment of human images caused by bounding box detection errors or
partial occlusions is one of the main challenges in person Re-Identification
(Re-ID) tasks. Previous local-based methods mainly focus on learning local
features in predefined semantic regions of pedestrians. These methods usually
use local hard alignment methods or introduce auxiliary information such as key
human pose points to match local features, which are often not applicable when
large scene differences are encountered. To solve these problems, we propose a
simple and efficient Local Sliding Alignment (LSA) strategy to dynamically
align the local features of two images by setting a sliding window on the local
stripes of the pedestrian. LSA can effectively suppress spatial misalignment
and does not need to introduce extra supervision information. Then, we design a
Global-Local Dynamic Feature Alignment Network (GLDFA-Net) framework, which
contains both global and local branches. We introduce LSA into the local branch
of GLDFA-Net to guide the computation of distance metrics, which can further
improve the accuracy of the testing phase. Evaluation experiments on several
mainstream evaluation datasets including Market-1501, DukeMTMC-reID, CUHK03 and
MSMT17 show that our method has competitive accuracy over the several
state-of-the-art person Re-ID methods. Specifically, it achieves 86.1% mAP and
94.8% Rank-1 accuracy on Market1501.

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The categories of this paper are: gr-qc
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The categories of this paper are: nlin
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The categories of this paper are: atom-ph
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The categories of this paper are: eess
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The categories of this paper are: chem-ph
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The categories of this paper are: comp-gas
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The categories of this paper are: nucl-th
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The categories of this paper are: cond-mat
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The categories of this paper are: acc-phys
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The categories of this paper are: ao-sci
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The categories of this paper are: quant-ph
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The categories of this paper are: physics
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The categories of this paper are: astro-ph
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The categories of this paper are: alg-geom
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The categories of this paper are: econ
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The categories of this paper are: stat