Tracking Performance Optimization
Tracking Performance Optimization is a methodological framework within virtual reality performance optimization that specifically enhances the accuracy, latency, and robustness of motion tracking systems by systematically minimizing computational overhead and sensor-derived errors in real-time user pose estimation.
195
Publications
9.2K
Citations
536
Authors
237
Institutions
Publications per year
2017–2026
87
195
A Twofold Siamese Network for Real-Time Object Tracking
Anfeng He, Chong Luo, Xinmei Tian et al. · 2018 · 661 citations
STMTrack: Template-free Visual Tracking with Space-time Memory Networks
Zhihong Fu, Qingjie Liu, Zehua Fu et al. · 2021 · 339 citations
Alpha-Refine: Boosting Tracking Performance by Precise Bounding Box Estimation
Bin Yan, Xinyu Zhang, Dong Wang et al. · 2021 · 225 citations
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237

University of Electronic Science and Technology of China
Chengdu, China
8 h-index
21 publications
844 citations

Harbin Institute of Technology
Harbin, China
6 h-index
20 publications
836 citations

Huazhong University of Science and Technology
Wuhan, China
6 h-index
15 publications
429 citations
Hubei Normal University
Huangshi, China
6 h-index
15 publications
412 citations

Xidian University
Xi'an, China
5 h-index
18 publications
1.7K citations

Chinese Academy of Sciences
Beijing, China
5 h-index
9 publications
203 citations
Syracuse University
Syracuse, United States
5 h-index
12 publications
807 citations
Tsinghua University
Beijing, China
5 h-index
14 publications
398 citations
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9 publications · 663 citations
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6 publications · 392 citations
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Repository · 7 publications · 173 citations
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4 publications · 341 citations
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2 publications · 88 citations
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