Papers
1
Total Citations
3
H-Index
1
About
Kewei Sun is a researcher in computer vision, with a primary focus on object tracking—a critical task for applications such as traffic monitoring, robotics, and autonomous vehicle navigation. His work centers on advancing discriminant tracking methods grounded in correlation filtering theory, which are valued for their high efficiency and robustness in dynamic visual environments. Sun’s most cited paper, "Correlation Filter-based Object Tracking Algorithms" (2020), has garnered 3 citations, reflecting its role in synthesizing and advancing progress in this fast-evolving field. By addressing key challenges in real-time performance and accuracy, his contributions help bridge the gap between theoretical tracking models and practical deployment in autonomous systems. Sun’s research continues to influence the development of more reliable and computationally efficient tracking solutions, making his work a valuable resource for students and engineers seeking to understand or innovate within correlation filter-based approaches.
Research Focus
Key Achievements
Top Papers
- 1Correlation Filter-based Object Tracking Algorithms3 citations · 2020