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Fitting procedural yarn models for realistic cloth rendering

Overview of attention for article published in ACM Transactions on Graphics, July 2016
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#15 of 1,700)
  • High Attention Score compared to outputs of the same age (96th percentile)
  • High Attention Score compared to outputs of the same age and source (90th percentile)

Mentioned by

news
11 news outlets

Citations

dimensions_citation
15 Dimensions

Readers on

mendeley
55 Mendeley
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Title
Fitting procedural yarn models for realistic cloth rendering
Published in
ACM Transactions on Graphics, July 2016
DOI 10.1145/2897824.2925932
Authors

Shuang Zhao, Fujun Luan, Kavita Bala

Mendeley readers

The data shown below were compiled from readership statistics for 55 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Chile 1 2%
United States 1 2%
Unknown 53 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 14 25%
Student > Master 13 24%
Researcher 9 16%
Student > Bachelor 7 13%
Other 4 7%
Other 4 7%
Unknown 4 7%
Readers by discipline Count As %
Computer Science 35 64%
Materials Science 3 5%
Engineering 3 5%
Physics and Astronomy 2 4%
Chemistry 2 4%
Other 2 4%
Unknown 8 15%

Attention Score in Context

This research output has an Altmetric Attention Score of 78. 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 31 August 2016.
All research outputs
#247,065
of 14,574,801 outputs
Outputs from ACM Transactions on Graphics
#15
of 1,700 outputs
Outputs of similar age
#8,265
of 262,369 outputs
Outputs of similar age from ACM Transactions on Graphics
#4
of 41 outputs
Altmetric has tracked 14,574,801 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,700 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.4. This one has done particularly well, scoring higher than 99% 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 262,369 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 96% of its contemporaries.
We're also able to compare this research output to 41 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 90% of its contemporaries.