Papers
2
Total Citations
9
H-Index
2
About
Weilong Li is a researcher specializing in computer vision, 3D perception, and intelligent sensing, with a focus on advancing calibration and segmentation techniques for real-world applications. His major contributions include developing a unified framework for hand-eye parameter estimation and line-structured light scanning calibration, a critical innovation for improving accuracy in robotic vision and industrial measurement systems. This work, published in 2024, has already garnered 6 citations, reflecting its timely relevance. Li is also the lead author of LessNet, a lightweight and efficient semantic segmentation architecture designed for large-scale outdoor point clouds. Introduced in 2022, LessNet addresses the pressing challenge of balancing computational efficiency with segmentation effectiveness in autonomous driving and robotics, earning 3 citations for its practical impact. By tackling both calibration and segmentation—two foundational pillars of 3D vision—Li’s research demonstrates a clear trajectory toward enabling more robust, real-time perception systems. His work is particularly notable for its emphasis on deployability, making advanced vision techniques accessible for resource-constrained platforms. As a rising voice in the field, Li’s contributions are shaping the next generation of intelligent sensing technologies.
Research Focus
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Top Papers
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