| Title |
Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotations
|
|---|---|
| Published in |
International Journal of Computer Vision, February 2017
|
| DOI | 10.1007/s11263-016-0981-7 |
| Authors |
Ranjay Krishna, Yuke Zhu, Oliver Groth, Justin Johnson, Kenji Hata, Joshua Kravitz, Stephanie Chen, Yannis Kalantidis, Li-Jia Li, David A. Shamma, Michael S. Bernstein, Li Fei-Fei |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 67% |
| United Kingdom | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 67% |
| Members of the public | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 1,328 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | <1% |
| Japan | 3 | <1% |
| United Kingdom | 2 | <1% |
| Singapore | 2 | <1% |
| Australia | 1 | <1% |
| India | 1 | <1% |
| Italy | 1 | <1% |
| Switzerland | 1 | <1% |
| Netherlands | 1 | <1% |
| Other | 2 | <1% |
| Unknown | 1311 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 318 | 24% |
| Student > Master | 221 | 17% |
| Researcher | 129 | 10% |
| Student > Bachelor | 104 | 8% |
| Other | 42 | 3% |
| Other | 148 | 11% |
| Unknown | 366 | 28% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 676 | 51% |
| Engineering | 132 | 10% |
| Linguistics | 18 | 1% |
| Agricultural and Biological Sciences | 14 | 1% |
| Physics and Astronomy | 14 | 1% |
| Other | 79 | 6% |
| Unknown | 395 | 30% |
Attention Score in Context
This research output has an Altmetric Attention Score of 11. 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 12 March 2024.
All research outputs
#3,232,015
of 26,017,215 outputs
Outputs from International Journal of Computer Vision
#115
of 1,452 outputs
Outputs of similar age
#62,568
of 431,419 outputs
Outputs of similar age from International Journal of Computer Vision
#1
of 12 outputs
Altmetric has tracked 26,017,215 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,452 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 particularly well, scoring higher than 92% 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 431,419 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 85% of its contemporaries.
We're also able to compare this research output to 12 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 91% of its contemporaries.