Shuping Ye

Suzhou University of Science and Technology

Papers

Total Citations

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About

Shuping Ye is a leading researcher in the field of visual simultaneous localization and mapping (VSLAM), with a primary focus on enhancing the robustness and accuracy of robotic perception in dynamic environments. Their most notable contribution, the DC-SLAM framework, introduces a novel dual-category dynamic feature suppression method for RGB-D VSLAM systems, effectively distinguishing between static and moving objects to improve localization stability in real-world, cluttered scenes. This work, published in 2025, has already garnered early citations, reflecting its timely relevance to autonomous navigation and augmented reality. Ye’s research addresses a critical bottleneck in VSLAM—handling dynamic elements like pedestrians or vehicles—by integrating geometric and semantic cues, offering a practical solution for applications ranging from service robotics to autonomous driving. With a growing citation impact, Shuping Ye is establishing a reputation for advancing the theoretical and practical boundaries of visual perception, making their work essential reading for students and engineers tackling the challenges of robust, real-time mapping and localization in unpredictable environments.