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SurRF: Unsupervised Multi-View Stereopsis by Learning Surface Radiance Field

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

  • Average Attention Score compared to outputs of the same age
  • Good Attention Score compared to outputs of the same age and source (65th percentile)

Mentioned by

twitter
2 X users

Citations

dimensions_citation
2 Dimensions

Readers on

mendeley
20 Mendeley
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Title
SurRF: Unsupervised Multi-View Stereopsis by Learning Surface Radiance Field
Published in
IEEE Transactions on Software Engineering, October 2022
DOI 10.1109/tpami.2021.3116695
Pubmed ID
Authors

Jinzhi Zhang, Mengqi Ji, Guangyu Wang, Zhiwei Xue, Shengjin Wang, Lu Fang

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 20 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 20%
Unspecified 2 10%
Professor > Associate Professor 1 5%
Student > Doctoral Student 1 5%
Lecturer 1 5%
Other 2 10%
Unknown 9 45%
Readers by discipline Count As %
Computer Science 6 30%
Unspecified 2 10%
Mathematics 1 5%
Engineering 1 5%
Unknown 10 50%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 05 October 2021.
All research outputs
#16,059,145
of 25,392,582 outputs
Outputs from IEEE Transactions on Software Engineering
#4,884
of 6,373 outputs
Outputs of similar age
#219,571
of 439,942 outputs
Outputs of similar age from IEEE Transactions on Software Engineering
#74
of 226 outputs
Altmetric has tracked 25,392,582 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 6,373 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 21st percentile – i.e., 21% of its peers scored the same or lower than it.
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 439,942 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 226 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 65% of its contemporaries.