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Disentangling Geometry and Appearance with Regularised Geometry-Aware Generative Adversarial Networks

Overview of attention for article published in International Journal of Computer Vision, March 2019
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About this Attention Score

  • Average Attention Score compared to outputs of the same age

Mentioned by

twitter
1 tweeter

Citations

dimensions_citation
1 Dimensions

Readers on

mendeley
14 Mendeley
Title
Disentangling Geometry and Appearance with Regularised Geometry-Aware Generative Adversarial Networks
Published in
International Journal of Computer Vision, March 2019
DOI 10.1007/s11263-019-01155-7
Authors

Linh Tran, Jean Kossaifi, Yannis Panagakis, Maja Pantic

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 14 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 36%
Researcher 4 29%
Unspecified 3 21%
Student > Master 1 7%
Other 1 7%
Other 0 0%
Readers by discipline Count As %
Computer Science 10 71%
Unspecified 3 21%
Agricultural and Biological Sciences 1 7%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 03 April 2019.
All research outputs
#8,259,804
of 13,172,054 outputs
Outputs from International Journal of Computer Vision
#574
of 655 outputs
Outputs of similar age
#150,621
of 253,036 outputs
Outputs of similar age from International Journal of Computer Vision
#2
of 4 outputs
Altmetric has tracked 13,172,054 research outputs across all sources so far. This one is in the 23rd percentile – i.e., 23% of other outputs scored the same or lower than it.
So far Altmetric has tracked 655 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 6th percentile – i.e., 6% 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 253,036 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 4 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.