Qingsheng Hu

Papers

Total Citations

H-Index

About

Qingsheng Hu’s research focuses on the intersection of machine vision, robotics, and spatial intelligence, with a particular emphasis on real-time perception and 3D reconstruction of indoor environments. His work addresses two critical challenges in autonomous systems: enabling machines to recognize and locate objects with high accuracy, and reconstructing dense, three-dimensional indoor scenes in real time. Hu’s 2021 paper on real-time object recognition and location has accumulated 4 citations, reflecting its relevance to advancing service robotics and industrial automation. His complementary study on real-time dense indoor scene reconstruction, which builds upon the ORB-SLAM2 framework, has earned 3 citations and demonstrates practical applications in augmented reality and cultural heritage preservation. By tackling the computational demands of simultaneous localization and mapping (SLAM) alongside object-level understanding, Hu contributes to bridging the gap between raw sensor data and actionable spatial knowledge. His work is particularly notable for its focus on real-time performance, a crucial requirement for deploying vision systems in dynamic, unstructured indoor settings.