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3D LiDAR and Stereo Fusion using Stereo Matching Network with Conditional Cost Volume Normalization

Overview of attention for article published in Proceedings of the IEEE RSJ International Conference on Intelligent Robots and Systems, January 2020
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#31 of 395)
  • High Attention Score compared to outputs of the same age (81st percentile)
  • High Attention Score compared to outputs of the same age and source (90th percentile)

Mentioned by

patent
5 patents

Readers on

mendeley
131 Mendeley
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Article details
Title
3D LiDAR and Stereo Fusion using Stereo Matching Network with Conditional Cost Volume Normalization
Published in
Proceedings of the IEEE RSJ International Conference on Intelligent Robots and Systems, January 2020
DOI 10.1109/iros40897.2019.8968170
Authors

Tsun-Hsuan Wang, Hou-Ning Hu, Chieh Hubert Lin, Yi-Hsuan Tsai, Wei-Chen Chiu, Min Sun

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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 131 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 131 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Master 32 24%
Student > Ph. D. Student 25 19%
Student > Doctoral Student 8 6%
Student > Bachelor 7 5%
Researcher 7 5%
Other 12 9%
Unknown 40 31%
Readers by discipline
Readers by discipline Count As %
Computer Science 42 32%
Engineering 41 31%
Mathematics 3 2%
Environmental Science 1 <1%
Biochemistry, Genetics and Molecular Biology 1 <1%
Other 1 <1%
Unknown 42 32%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 25 November 2025.
All research outputs
#5,194,069
of 34,640,154 outputs
Outputs from Proceedings of the IEEE RSJ International Conference on Intelligent Robots and Systems
#31
of 395 outputs
Outputs of similar age
#94,086
of 522,149 outputs
Outputs of similar age from Proceedings of the IEEE RSJ International Conference on Intelligent Robots and Systems
#19
of 276 outputs
Altmetric has tracked 34,640,154 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 395 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one has done well, scoring higher than 88% 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 522,149 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 81% of its contemporaries.
We're also able to compare this research output to 276 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.