Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Occluded Person Re-identification   Person re-identification (re-id) suffers from a serious occlusion problem
when applied to crowded public places. In this paper, we propose to retrieve a
full-body person image by using a person image with occlusions. This differs
significantly from the conventional person re-id problem where it is assumed
that person images are detected without any occlusion. We thus call this new
problem the occluded person re-identitification. To address this new problem,
we propose a novel Attention Framework of Person Body (AFPB) based on deep
learning, consisting of 1) an Occlusion Simulator (OS) which automatically
generates artificial occlusions for full-body person images, and 2) multi-task
losses that force the neural network not only to discriminate a person's
identity but also to determine whether a sample is from the occluded data
distribution or the full-body data distribution. Experiments on a new occluded
person re-id dataset and three existing benchmarks modified to include
full-body person images and occluded person images show the superiority of the
proposed method.

8
The categories of this paper are: hep-ex
16
The categories of this paper are: stat
15
The categories of this paper are: nucl-ex
11
The categories of this paper are: hep-lat
6
The categories of this paper are: astro-ph
3
The categories of this paper are: physics
0
The categories of this paper are: hep-ph
19
The categories of this paper are: eess
24
The categories of this paper are: dg-ga
28
The categories of this paper are: alg-geom
32
The categories of this paper are: atom-ph
31
The categories of this paper are: ao-sci
14
The categories of this paper are: math-ph
26
The categories of this paper are: bayes-an
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The categories of this paper are: nlin
12
The categories of this paper are: nucl-th