Young Min Kim

Seoul National University, Stanford University

Papers

Total Citations

H-Index

About

Young Min Kim is a leading researcher in 3D computer vision and robotics, with a focus on automating the acquisition and understanding of three-dimensional environments. Her work bridges the gap between raw sensor data and practical, high-fidelity 3D models. A key contribution is her development of automatic pose generation for robotic 3-D scanning systems, enabling efficient and precise reverse engineering of mechanical parts—a paper that has garnered 41 citations. She has also advanced real-time scanning of indoor objects, addressing the critical challenges of noisy and incomplete raw scans to facilitate semantic scene understanding, with 32 citations. More recently, her research on calibrating panoramic depth estimation has opened new avenues for practical localization and mapping, demonstrating how accurate depth from panoramic images can serve as a lightweight yet powerful input for assistive technologies. Kim’s work is notable for its direct impact on robotics, augmented reality, and autonomous navigation, consistently pushing the boundaries of how machines perceive and interact with complex, real-world spaces.