Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Pose-guided Visible Part Matching for Occluded Person ReID   Occluded person re-identification is a challenging task as the appearance
varies substantially with various obstacles, especially in the crowd scenario.
To address this issue, we propose a Pose-guided Visible Part Matching (PVPM)
method that jointly learns the discriminative features with pose-guided
attention and self-mines the part visibility in an end-to-end framework.
Specifically, the proposed PVPM includes two key components: 1) pose-guided
attention (PGA) method for part feature pooling that exploits more
discriminative local features; 2) pose-guided visibility predictor (PVP) that
estimates whether a part suffers the occlusion or not. As there are no ground
truth training annotations for the occluded part, we turn to utilize the
characteristic of part correspondence in positive pairs and self-mining the
correspondence scores via graph matching. The generated correspondence scores
are then utilized as pseudo-labels for visibility predictor (PVP). Experimental
results on three reported occluded benchmarks show that the proposed method
achieves competitive performance to state-of-the-art methods. The source codes
are available at https://github.com/hh23333/PVPM

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The categories of this paper are: quant-ph
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The categories of this paper are: econ
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The categories of this paper are: hep-lat
32
The categories of this paper are: atom-ph
34
The categories of this paper are: chem-ph
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The categories of this paper are: hep-th
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The categories of this paper are: nucl-th
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The categories of this paper are: funct-an
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The categories of this paper are: gr-qc
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The categories of this paper are: q-bio
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The categories of this paper are: math
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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: cmp-lg
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The categories of this paper are: solv-int
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The categories of this paper are: chao-dyn