Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Imitating Targets from all sides: An Unsupervised Transfer Learning
  method for Person Re-identification   Person re-identification (Re-ID) models usually show a limited performance
when they are trained on one dataset and tested on another dataset due to the
inter-dataset bias (e.g. completely different identities and backgrounds) and
the intra-dataset difference (e.g. camera invariance). In terms of this issue,
given a labelled source training set and an unlabelled target training set, we
propose an unsupervised transfer learning method characterized by 1) bridging
inter-dataset bias and intra-dataset difference via a proposed ImitateModel
simultaneously; 2) regarding the unsupervised person Re-ID problem as a
semi-supervised learning problem formulated by a dual classification loss to
learn a discriminative representation across domains; 3) exploiting the
underlying commonality across different domains from the class-style space to
improve the generalization ability of re-ID models. Extensive experiments are
conducted on two widely employed benchmarks, including Market-1501 and
DukeMTMC-reID, and experimental results demonstrate that the proposed method
can achieve a competitive performance against other state-of-the-art
unsupervised Re-ID approaches.

11
The categories of this paper are: hep-lat
10
The categories of this paper are: q-bio
34
The categories of this paper are: chem-ph
28
The categories of this paper are: alg-geom
13
The categories of this paper are: quant-ph
6
The categories of this paper are: astro-ph
9
The categories of this paper are: nlin
36
The categories of this paper are: cmp-lg
15
The categories of this paper are: nucl-ex
0
The categories of this paper are: hep-ph
26
The categories of this paper are: bayes-an
23
The categories of this paper are: solv-int
4
The categories of this paper are: cond-mat
5
The categories of this paper are: gr-qc
37
The categories of this paper are: supr-con
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The categories of this paper are: math-ph