Jiung Yeon

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About

Jiung Yeon is a rising researcher in computer vision and robotics, whose work centers on advancing dense 3D scene representation for Simultaneous Localization and Mapping (SLAM). His most notable contribution, "RGBD GS-ICP SLAM" (2024), has already garnered over 50 citations, underscoring its rapid impact. This work bridges neural scene representation and 3D Gaussian splatting to achieve robust, real-time dense mapping from RGB-D data—a critical capability for applications in robotics, Virtual Reality (VR), and Augmented Reality (AR). By integrating iterative closest point (ICP) alignment with Gaussian-based rendering, Yeon’s method improves both localization accuracy and map fidelity, addressing long-standing challenges in dynamic environments. His research pushes the boundaries of how machines perceive and reconstruct complex spaces, offering a practical pathway toward more immersive AR/VR experiences and autonomous navigation. As an early-career scholar, Yeon’s high citation velocity signals his work’s growing influence, positioning him as a key voice in the next wave of dense SLAM innovation.