Papers
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Total Citations
2
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About
Runze Wei is a robotics researcher focused on advancing vision-based human-robot interaction, with a particular emphasis on person-following capabilities for service robots. His work addresses a critical challenge in autonomous robotics: enabling robots to reliably track and follow individuals in dynamic environments without relying on massive pre-labeled training datasets. Wei’s most cited paper, "Tracking by segmentation with future motion estimation applied to person-following robots" (2023), introduces a novel tracking-by-segmentation approach that integrates future motion estimation, reducing dependency on traditional tracking-by-detection methods that require extensive data for training. This contribution is significant for improving real-time performance and robustness in applications like assistive robotics and autonomous navigation. While his citation count is still growing—with 2 citations on this key work—Wei’s research represents an important step toward more efficient, data-light solutions in robotic perception. His work is particularly relevant for students and researchers interested in computer vision, robot learning, and the practical deployment of service robots in human-centered environments.
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Top Papers
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