Stereo Visual Slam
Stereo Visual SLAM is a visual simultaneous localization and mapping framework that employs stereoscopic camera inputs to jointly estimate the camera trajectory and reconstruct the three-dimensional environment by exploiting parallax for metric depth estimation.
195
Publications
29.4K
Citations
607
Authors
229
Institutions
Publications per year
2017–2026
108
Parents
195
Are we ready for autonomous driving? The KITTI vision benchmark suite
Andreas Geiger, P Lenz, R. Urtasun · 2012 · 14.4K citations
DynaSLAM: Tracking, Mapping and Inpainting in Dynamic Scenes
Berta Bescos, José M. Fácil, Javier Civera et al. · Zaguan (Universidad de Zaragoza) · 2018 · 924 citations · Full text
1–5 of 195
607
Centro Internacional Franco-Argentino de Ciencias de la Información y de Sistemas, Argentina
5 publications · 351 citations
5
h-index
5
h-index
5
h-index
Laboratoire d'Analyse et d'Architecture des Systèmes, France
5 publications · 368 citations
5
h-index
4
h-index
1–5 of 607
229
Tsinghua University
Beijing, China
8 h-index
24 publications
1K citations

Centre National de la Recherche Scientifique
Paris, France
6 h-index
16 publications
1.4K citations
Carnegie Mellon University
Pittsburgh, United States
6 h-index
23 publications
3K citations
Korea Advanced Institute of Science and Technology
Daejeon, South Korea
6 h-index
15 publications
470 citations
Universidad de Zaragoza
Zaragoza, Spain
6 h-index
16 publications
23.2K citations
Université Paris-Saclay
Gif-sur-Yvette, France
5 h-index
16 publications
889 citations
University of Technology Sydney
Sydney, Australia
5 h-index
14 publications
299 citations
University of Chinese Academy of Sciences
Beijing, China
4 h-index
7 publications
150 citations
1–8 of 229
11 publications · 468 citations
11
h-index
10 publications · 374 citations
10
h-index
8 publications · 199 citations
8
h-index
5 publications · 157 citations
5
h-index
4 publications · 133 citations
4
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1–5