Xiaojuan Ning

Papers

Total Citations

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About

Xiaojuan Ning is a researcher specializing in 3D scene understanding, geometric shape analysis, and ecological informatics. Her work bridges computer vision and environmental modeling, with a focus on extracting semantic structure from point cloud data. In her foundational 2013 paper, Ning introduced a method for classifying object shapes and representing scene geometry in 3D laser-scanned outdoor environments, enabling applications in city planning, robot navigation, and virtual tourism. This work, cited 8 times, established her as a contributor to semantic 3D scene parsing. More recently, she has advanced indoor modeling with a slicing-components approach for vectorized object reconstruction from unilateral point clouds (2022, 3 citations), and pushed into ecological applications with a boundary-aware instance segmentation method for trees and shrubs using structural probability analysis (2025, 2 citations). Her research demonstrates a consistent trajectory from coarse scene-level shape representation to fine-grained, object-level modeling, with growing relevance to autonomous systems and environmental monitoring. Ning’s work is notable for its practical orientation toward real-world sensor data, making her contributions valuable for researchers in 3D computer vision, robotics, and ecological remote sensing.