Khiem Vuong

University of Minnesota, University of Minnesota System

Papers

Total Citations

H-Index

About

Khiem Vuong is a researcher advancing the field of computer vision, with a core focus on 3D scene understanding and geometric deep learning. His most notable contribution is the development of the **spatial rectifier**, a novel approach for estimating surface normals from tilted images—a critical challenge as visual data is increasingly captured by arbitrarily oriented sensors on robots, drones, and body-mounted cameras. Vuong’s work directly addresses the performance limitations of traditional methods, which struggle with off-axis perspectives. His key publication on this topic has accumulated **36 citations** to date, reflecting its growing influence in the vision community. By enabling more robust 3D reconstruction from non-ideal camera angles, Vuong’s research has practical implications for autonomous navigation, augmented reality, and robotic perception. His work stands out for tackling a real-world problem often overlooked in standard benchmark datasets, positioning him as a thoughtful contributor to making computer vision systems more adaptable and reliable in dynamic environments.