Tracking Evaluation Metrics is a standardized methodological framework used in computer vision to quantitatively assess the performance of visual tracking algorithms by measuring the accuracy, robustness, and temporal consistency of predicted target trajectories relative to ground-truth annotations.
321
Publications
45.8K
Citations
1.5K
Authors
468
Institutions
Publications per year
2017–2026
144
Parents
Publications
321
Online Object Tracking: A Benchmark
Yi Wu, Jongwoo Lim, Ming–Hsuan Yang · 2013 · 4.1K citations
LaSOT: A High-Quality Benchmark for Large-Scale Single Object Tracking
Heng Fan, Liting Lin, Fan Yang et al. · 2019 · 1.6K citations
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- MK
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- LL
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- HL
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1–5 of 1.5K
Institutions
468
Carnegie Mellon University
Pittsburgh, United States
12 h-index
40 publications
7.2K citations
Chinese Academy of Sciences
Beijing, China
10 h-index
90 publications
33.4K citations
Zhejiang University
Hangzhou, China
9 h-index
26 publications
6.7K citations
University of Chinese Academy of Sciences
Beijing, China
9 h-index
30 publications
10.2K citations
University of Ljubljana
Ljubljana, Slovenia
9 h-index
29 publications
9.2K citations
University of Oxford
Oxford, United Kingdom
8 h-index
28 publications
8.8K citations
RWTH Aachen University
Aachen, Germany
8 h-index
22 publications
4.8K citations
Linköping University
Linköping, Sweden
8 h-index
27 publications
12.2K citations
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Venues
- arXiv (Cornell University)
Repository · 28 publications · 4K citations
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- IEEE Transactions on Pattern Analysis and Machine Intelligence
TPAMI · 12 publications · 8.5K citations
12
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- Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE
15 publications · 419 citations
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- IEEE Transactions on Image Processing
9 publications · 1.4K citations
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- International Journal of Computer Vision
6 publications · 1.7K citations
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