Zehua Liu

Papers

Total Citations

H-Index

About

Dr. Zehua Liu is a rising researcher in computer vision and robotics, with a primary focus on 3D point cloud registration—a critical task for reverse engineering, autonomous navigation, and augmented reality. His most cited work, "HDRNet: High‐Dimensional Regression Network for Point Cloud Registration" (2022), introduces a novel learning-based framework that leverages high-dimensional regression to estimate accurate transformation matrices for aligning source and target point clouds. This approach addresses key limitations of traditional methods, such as sensitivity to noise and partial overlaps, by learning robust feature correspondences directly from data. With 7 citations, the paper has already garnered attention for its potential to improve real-time registration in complex environments. Liu’s contributions are particularly notable for bridging deep learning with geometric processing, offering a scalable solution that outperforms classical algorithms on benchmark datasets. As an early-career scholar, his work signals a promising trajectory in advancing 3D perception systems, with implications for robotics, autonomous driving, and digital twin creation.