Zhenzhong Wei

Papers

Total Citations

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About

Zhenzhong Wei is a leading researcher in computer vision and robotics, with a focus on 6D pose estimation and robot vision system calibration. His most impactful work, "NVR-Net: Normal Vector Guided Regression Network for Disentangled 6D Pose Estimation" (2023, 19 citations), introduces a novel deep learning approach that decouples rotation and translation estimation for monocular 6D pose estimation, overcoming accuracy limitations of traditional PnP-based methods. This work is critical for applications in augmented reality, autonomous manipulation, and industrial robotics. Wei’s foundational contributions to robot calibration include a 2013 paper (9 citations) that uses laser trackers to calibrate robot twist angles by fitting planes to measured positions, significantly improving visual measurement system accuracy. Earlier, in 2008 (2 citations), he proposed an extended eye-in-hand calibration method using an assistant camera to solve object-to-camera pose problems in robotic hand-eye systems. His research bridges classical calibration techniques with modern deep learning, enabling more precise and disentangled pose estimation for real-world robotics. With a career spanning over a decade, Wei’s work continues to influence both theoretical advancements and practical implementations in intelligent robotics and computer vision.