Xingyu Jiang

Wuhan University, Southern University of Science and Technology

Papers

Total Citations

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About

Xingyu Jiang is a leading researcher in robotics and computer vision, with a core focus on simultaneous localization and mapping (SLAM) and human motion capture. His most influential work, the 2021 paper on "Appearance-Based Loop Closure Detection via Locality-Driven Accurate Motion Field Learning" (22 citations), tackles a fundamental challenge in SLAM: enabling robots to reliably recognize previously visited locations. Jiang’s innovative two-step strategy, which leverages accurate motion field learning, significantly improves loop closure detection—a critical capability for autonomous navigation in complex environments. More recently, Jiang has advanced human-computer interaction with the "CST Framework: A Robust and Portable Finger Motion Tracking Framework" (2024, 4 citations). This work addresses the cumbersome calibration and heavy hardware typical of finger tracking, proposing a lightweight, robust solution that captures subtle joint movements. By bridging robust robotic perception and intuitive human motion tracking, Jiang’s research is paving the way for more autonomous robots and seamless wearable interfaces. His contributions are particularly valuable for students and researchers exploring SLAM, motion capture, and the intersection of robotics with assistive technology.