Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Hybrid Contrastive Learning with Cluster Ensemble for Unsupervised
  Person Re-identification   Unsupervised person re-identification (ReID) aims to match a query image of a
pedestrian to the images in gallery set without supervision labels. The most
popular approaches to tackle unsupervised person ReID are usually performing a
clustering algorithm to yield pseudo labels at first and then exploit the
pseudo labels to train a deep neural network. However, the pseudo labels are
noisy and sensitive to the hyper-parameter(s) in clustering algorithm. In this
paper, we propose a Hybrid Contrastive Learning (HCL) approach for unsupervised
person ReID, which is based on a hybrid between instance-level and
cluster-level contrastive loss functions. Moreover, we present a
Multi-Granularity Clustering Ensemble based Hybrid Contrastive Learning
(MGCE-HCL) approach, which adopts a multi-granularity clustering ensemble
strategy to mine priority information among the pseudo positive sample pairs
and defines a priority-weighted hybrid contrastive loss for better tolerating
the noises in the pseudo positive samples. We conduct extensive experiments on
two benchmark datasets Market-1501 and DukeMTMC-reID. Experimental results
validate the effectiveness of our proposals.

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The categories of this paper are: hep-ex
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The categories of this paper are: plasm-ph
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The categories of this paper are: funct-an
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The categories of this paper are: quant-ph
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The categories of this paper are: ao-sci
20
The categories of this paper are: acc-phys
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The categories of this paper are: hep-th
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The categories of this paper are: astro-ph
22
The categories of this paper are: chao-dyn
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The categories of this paper are: stat
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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: patt-sol
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The categories of this paper are: q-fin
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The categories of this paper are: eess
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The categories of this paper are: cond-mat