Computer Vision – ECCV 2020
Springer International Publishing
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X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
Learning to Predict Salient Faces: A Novel Visual-Audio Saliency Model
|
|---|---|
| Book title |
Computer Vision – ECCV 2020
|
| Published in |
arXiv, November 2020
|
| DOI | 10.1007/978-3-030-58565-5_25 |
| Book ISBNs |
978-3-03-058564-8, 978-3-03-058565-5
|
| Authors |
Yufan Liu, Minglang Qiao, Mai Xu, Bing Li, Weiming Hu, Ali Borji, Liu, Yufan, Qiao, Minglang, Xu, Mai, Li, Bing, Hu, Weiming, Borji, Ali |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 51 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 9 | 18% |
| Student > Master | 9 | 18% |
| Researcher | 3 | 6% |
| Student > Bachelor | 1 | 2% |
| Librarian | 1 | 2% |
| Other | 2 | 4% |
| Unknown | 26 | 51% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 18 | 35% |
| Engineering | 4 | 8% |
| Economics, Econometrics and Finance | 1 | 2% |
| Agricultural and Biological Sciences | 1 | 2% |
| Unknown | 27 | 53% |
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 30 March 2021.
All research outputs
#15,660,371
of 23,270,775 outputs
Outputs from arXiv
#381,719
of 958,494 outputs
Outputs of similar age
#255,533
of 415,478 outputs
Outputs of similar age from arXiv
#13,851
of 35,495 outputs
Altmetric has tracked 23,270,775 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 958,494 research outputs from this source. They receive a mean Attention Score of 3.9. This one has gotten more attention than average, scoring higher than 53% 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 415,478 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 29th percentile – i.e., 29% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 35,495 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 54% of its contemporaries.