Point Cloud Tracking
Point Cloud Tracking is a computational method in point cloud processing that dynamically associates and follows the spatial-temporal evolution of three-dimensional point sets across consecutive frames to estimate object motion and trajectory.
250
Publications
16K
Citations
773
Authors
299
Institutions
Publications per year
2017–2026
115
Parents
250
Deep Learning for 3D Point Clouds: A Survey
Yulan Guo, Hanyun Wang, Qingyong Hu et al. · IEEE Transactions on Pattern Analysis and Machine Intelligence · 2020 · 2.3K citations
Center-based 3D Object Detection and Tracking
Tianwei Yin, Xingyi Zhou, Philipp Krähenbühl · 2021 · 1.9K citations
Fusing points and lines for high performance tracking
Edward Rosten, Tom Drummond · 2005 · 1.1K citations
1–5 of 250
773
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299
Technical University of Munich
Munich, Germany
9 h-index
20 publications
789 citations
Tsinghua University
Beijing, China
8 h-index
13 publications
434 citations
Stanford University
Stanford, United States
5 h-index
17 publications
769 citations

National University of Defense Technology
Changsha, China
5 h-index
12 publications
4.7K citations

Northeastern University
Shenyang, China
5 h-index
19 publications
977 citations

The University of Western Australia
Perth, Australia
4 h-index
8 publications
2.6K citations
Carnegie Mellon University
Pittsburgh, United States
4 h-index
7 publications
1K citations
University of California, Berkeley
Berkeley, United States
4 h-index
14 publications
1.3K citations
1–8 of 299
Repository · 11 publications · 327 citations
10
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8 publications · 513 citations
8
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TPAMI · 6 publications · 2.5K citations
6
h-index
5 publications · 564 citations
5
h-index
5 publications · 227 citations
5
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