BRIEF: Binary Robust Independent Elementary Features
2010 • 5996 Citations
Published in 11th European Conference on Computer Vision (ECCV 2010)
Vincent Lepetit
Vincent Lepetit is a researcher affiliated with Ecole des Ponts ParisTech, specializing in AI & Machine Learning. Their work has been cited 48,224 times. This profile visualizes their global influence, highlighting strong citation networks in CN.
AI & Machine Learning
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Vincent Lepetit's Citation Metrics
Bibliometric impact based on 1 indexed publication.
- H-Index
- 1
- i10-Index
- 1
- Total Citations
- 48,224
- Citing Countries
- 3
As of April 2026.
Vincent Lepetit has an h-index of 1 and 48,224 total citations across 1 publication, with research cited by institutions in 3 countries.
Global Impact Map
Visualizing the geographic distribution of institutions that have cited your work.
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Top Citing Countries(Limited)
China(CN)
5Spain(ES)
3Hong Kong(HK)
3Top Citing Institutions(Limited)
Wuhan University
3Hong Kong University of Science and Technology
3Universidad de Zaragoza
3Harbin Institute of Technology
1Shanghai Jiao Tong University
1Visa Evidence Package
Views and exports tuned for EB-1A, O-1A, and EB-2 NIW petitions. Sustained acclaim, geographic reach, and independent-citation filtering are the strongest evidence categories immigration adjudicators look for.
Citer Influence Network
Visa-ready visualisation: each outer ring node is a country citing this scholar. Node size & edge weight scale with citing-paper count. Showing top 3 of 3 countries (11 total citations).
Letter of Support — Candidate Recommenders
Ranked by EB-1A / O-1A relevance: independence from your home institution, affiliation with a top-ranked institution, repeat citations of your work, and recency. Reach out to the highest-scoring candidates to request support letters.
- #1
Peiliang Li
8.5Hong Kong University of Science and Technology
Hong Kong· Cited your work 1 time
IndependentTop institutionDiversifies geography - #2
Shaojie Shen
8.5Hong Kong University of Science and Technology
Hong Kong· Cited your work 1 time
IndependentTop institutionDiversifies geography - #3
Junjun Jiang
7.0Harbin Institute of Technology
China· Cited your work 1 time
IndependentTop institution - #4
Junchi Yan
7.0Shanghai Jiao Tong University
China· Cited your work 1 time
IndependentTop institution - #5
Raúl Mur-Artal
6.5Universidad de Zaragoza
Spain· Cited your work 1 time
IndependentDiversifies geography - #6
José María Martínez Montiel
6.5Universidad de Zaragoza
Spain· Cited your work 1 time
IndependentDiversifies geography - #7
Tong Qin
8.5Hong Kong University of Science and Technology
Hong Kong· Cited your work 1 time
IndependentTop institutionDiversifies geography - #8
Aoxiang Fan
5.0Wuhan University
China· Cited your work 1 time
Independent - #9
Jiayi Ma
5.0Wuhan University
China· Cited your work 1 time
Independent - #10
Xingyu Jiang
5.0Wuhan University
China· Cited your work 1 time
Independent
Scores combine 5 signals: independence (+3), prestige institution (+2), repeat citations (+2 per paper, cap 5), recent activity (+1), and geography diversity (+1.5). Identity matching uses name + institution; namesakes at the same org are merged.
Cited by 5 papers
5 / 5 independent
Citations flagged as non-independent share the scholar's home institution (École Polytechnique Fédérale de Lausanne). EB-1A & O-1A petitions typically quote the independent-citation count as the stronger evidence of outside recognition.
· cites “BRIEF: Binary Robust Independent Elementary Features”
· cites “BRIEF: Binary Robust Independent Elementary Features”
Tong Qin, Peiliang Li, Shaojie Shen
IEEE Transactions on Robotics· cites “BRIEF: Binary Robust Independent Elementary Features”
Jiayi Ma, Xingyu Jiang, Aoxiang Fan, Junjun Jiang + 1 more
International Journal of Computer Vision (IJCV)· cites “BRIEF: Binary Robust Independent Elementary Features”
Raúl Mur-Artal, José María Martínez Montiel, Juan Domingo Tardós Solano
IEEE Transactions on Robotics (T-RO)· cites “BRIEF: Binary Robust Independent Elementary Features”
Top Cited Works(Showing 1 of 1)
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Citation Trend (Last 10 Years)
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