Multi-camera Visual Slam
Multi-Camera Visual SLAM is a visual simultaneous localization and mapping framework that utilizes inputs from multiple cameras with varied configurations to jointly estimate ego-motion and reconstruct the environment, distinguished by its integration of multi-perspective visual data to enhance robustness and coverage compared to single-camera systems.
38
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2K
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140
Authors
53
Institutions
Publications per year
2017–2026
18
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38
Fast relocalisation and loop closing in keyframe-based SLAM
Raul Mur-Artal, Juan D. Tardós · 2014 · 265 citations
A survey on Visual-Based Localization: On the benefit of heterogeneous data
Nathan Piasco, Désiré Sidibé, Cédric Demonceaux et al. · Pattern Recognition · 2017 · 230 citations
InteriorNet: Mega-scale Multi-sensor Photo-realistic Indoor Scenes\n Dataset
Wenbin Li, Sajad Saeedi, John McCormac et al. · arXiv (Cornell University) · 2018 · 104 citations · Full text
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ETH Zurich
Zurich, Switzerland
6 h-index
17 publications
1.3K citations

University of Tübingen
Tübingen, Germany
3 h-index
8 publications
264 citations

University of Waterloo
Waterloo, Canada
3 h-index
5 publications
96 citations
National University of Singapore
Singapore, Singapore
3 h-index
3 publications
368 citations
DSO National Laboratories
Singapore, Singapore
3 h-index
3 publications
368 citations

Imperial College London
London, United Kingdom
2 h-index
9 publications
1K citations
University of Zurich
Zurich, Switzerland
2 h-index
8 publications
376 citations
Georgia Institute of Technology
Atlanta, United States
2 h-index
3 publications
138 citations
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2 publications · 23 citations
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Repository · 2 publications · 124 citations
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CVIU · 2 publications · 88 citations
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2 publications · 138 citations
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Repository · 1 publications · 51 citations
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