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Deep Learning for Person Re-Identification: A Survey and Outlook

Overview of attention for article published in IEEE Transactions on Software Engineering, May 2022
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (88th percentile)
  • High Attention Score compared to outputs of the same age and source (86th percentile)

Mentioned by

patent
21 patents

Readers on

mendeley
1001 Mendeley
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Article details
Title
Deep Learning for Person Re-Identification: A Survey and Outlook
Published in
IEEE Transactions on Software Engineering, May 2022
DOI 10.1109/tpami.2021.3054775
Pubmed ID
Authors

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Timeline Attention over time Attention Score history
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Activity
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Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 1,001 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 1001 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Master 126 13%
Student > Ph. D. Student 109 11%
Student > Bachelor 65 6%
Researcher 52 5%
Student > Postgraduate 34 3%
Other 87 9%
Unknown 528 53%
Readers by discipline
Readers by discipline Count As %
Computer Science 303 30%
Engineering 86 9%
Mathematics 9 <1%
Social Sciences 7 <1%
Agricultural and Biological Sciences 6 <1%
Other 41 4%
Unknown 549 55%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 15. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 21 May 2026.
All research outputs
#3,052,484
of 34,601,305 outputs
Outputs from IEEE Transactions on Software Engineering
#431
of 7,941 outputs
Outputs of similar age
#53,651
of 470,788 outputs
Outputs of similar age from IEEE Transactions on Software Engineering
#11
of 82 outputs
Altmetric has tracked 34,601,305 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,941 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.0. This one has done particularly well, scoring higher than 93% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 470,788 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 88% of its contemporaries.
We're also able to compare this research output to 82 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 86% of its contemporaries.