Ransac
Ransac is an iterative model estimation method that distinguishes itself by robustly fitting a mathematical model to observed data containing outliers through random sampling of minimal subsets and consensus evaluation.
470
Publications
54.4K
Citations
1.3K
Authors
471
Institutions
Publications per year
2017–2026
170
Variants
Random Sample Consensus
Parents
470
Martin A. Fischler, Robert C. Bolles · Communications of the ACM · 1981 · 25.5K citations · Full text
Matching with PROSAC — Progressive Sample Consensus
Ondřej Chum, Jiřı́ Matas · 2005 · 1.1K citations · Full text
Scene Coordinate Regression Forests for Camera Relocalization in RGB-D Images
Jamie Shotton, Ben Glocker, Christopher Zach et al. · 2013 · 951 citations
MUlti-Store Tracker (MUSTer): A cognitive psychology inspired approach to object tracking
Zhibin Hong, Zhe Chen, Chaohui Wang et al. · 2015 · 683 citations
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471

Czech Technical University in Prague
Prague, Czechia
16 h-index
35 publications
6.5K citations
Wuhan University
Wuhan, China
15 h-index
44 publications
4.3K citations

Lund University
Lund, Sweden
10 h-index
28 publications
798 citations
ETH Zurich
Zurich, Switzerland
10 h-index
19 publications
1.4K citations

Centre National de la Recherche Scientifique
Paris, France
9 h-index
17 publications
1.3K citations
State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing
Wuhan, China
7 h-index
11 publications
1K citations

Zhejiang University
Hangzhou, China
6 h-index
15 publications
792 citations
Tsinghua University
Beijing, China
6 h-index
10 publications
406 citations
1–8 of 471
TPAMI · 14 publications · 2K citations
14
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11 publications · 332 citations
12
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12 publications · 997 citations
11
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8 publications · 126 citations
9
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5 publications · 128 citations
5
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