Xueying Sun

Papers

Total Citations

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About

Xueying Sun is a researcher specializing in computer vision and robotic systems, with a particular focus on object detection and instance recognition in applied automation contexts. Her notable work includes the development of a dual-layer density estimation architecture for multiple object instance detection, published in 2016, which addresses the practical challenges of robot inventory management. This innovative approach combines raw scale-invariant feature transform (SIFT) feature matching with keypoint projection techniques, enabling robust and scale-aware detection of multiple object instances in complex real-world environments. By leveraging dominant scale ratios within a layered density estimation framework, her method offers a meaningful advancement in how robots can autonomously identify and manage inventory items — a problem with significant industrial relevance. While her citation record reflects an emerging body of work, her research bridges fundamental computer vision methodology with tangible robotic applications, demonstrating a commitment to translating algorithmic innovation into practical deployment. Her contributions are of particular interest to students and researchers working at the intersection of machine perception, feature-based recognition, and intelligent robotic systems seeking scalable solutions for real-world object detection tasks.