Hui Ma

Chinese University of Hong Kong, Shenzhen, Hong Kong Baptist University

Papers

Total Citations

H-Index

About

Hui Ma is a researcher specializing in computer vision and robotics, with a particular focus on 6D pose estimation, hand-eye calibration, and vision-based measurement systems. Her work sits at the intersection of deep learning and practical robotic applications, addressing fundamental challenges in how machines perceive and interact with the physical world. Ma's most notable contribution, "Real-Time and Efficient 6-D Pose Estimation From a Single RGB Image" (2021), has garnered 40 citations and represents a significant advance in the field. By leveraging deep neural networks to directly predict 2D projection positions of 3D object keypoints from a single RGB image, her approach offers both computational efficiency and real-time capability — qualities essential for deployment in robotics, autonomous driving, and augmented reality applications. Her more recent work, "HCNV: Hand-Eye Calibration Based on Surface Normal Optimization and View Selection" (2025), demonstrates a continued commitment to pushing beyond existing limitations. By incorporating geometric features such as surface normals into the calibration pipeline — rather than relying solely on point clouds — Ma addresses a persistent blind spot in robotic perception research. Overall, Ma's contributions reflect a researcher dedicated to making computer vision systems more precise, efficient, and practically deployable across real-world robotic environments.