Xiaoxiu Zhu

Papers

Total Citations

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About

Driven by the challenges of autonomous navigation and large-scale environmental mapping, Xiaoxiu Zhu focuses on advancing 3D point cloud registration for outdoor scenes. Her most influential work introduces PYRF-PCR, a robust three-stage registration framework that overcomes the limitations of existing methods, which often falter under large rotations or poor generalization. By integrating a novel pipeline, Zhu’s approach significantly improves alignment accuracy and reliability in complex, real-world environments—a critical step for photogrammetry, remote sensing, and robotic perception. With her top-cited paper accumulating 46 citations since 2023, Zhu’s contributions are already shaping how researchers tackle outdoor point cloud processing. Her work stands out for its practical robustness, offering a scalable solution that bridges the gap between theoretical registration algorithms and deployment in dynamic, unstructured settings. As a rising voice in this domain, Zhu continues to push the boundaries of 3D vision, making her research essential reading for students and engineers working on autonomous systems and geospatial data analysis.