Howoong Jun
Papers
1
Total Citations
3
H-Index
1
About
Howoong Jun is a researcher at the forefront of autonomous navigation and augmented reality, specializing in street-level localization and 3D scene representation. His most notable contribution is the pioneering work "Renderable Street View Map-Based Localization: Leveraging 3D Gaussian Splatting for Street-Level Positioning" (2024), which introduces the first application of 3D Gaussian splatting to the critical challenge of robust, real-world localization. This innovative approach enables precise positioning for autonomous vehicles, AR navigation, and outdoor mobile robots by creating renderable street-view maps that bridge the gap between synthetic models and complex urban environments. Though early in its impact, the paper has already garnered 3 citations, signaling strong interest from the computer vision and robotics communities. Jun’s work addresses a fundamental bottleneck in outdoor mobile systems, offering a scalable solution that combines photorealistic rendering with high-accuracy localization. His research promises to advance the reliability of autonomous systems in dynamic, GPS-denied settings, making him a rising voice in the intersection of 3D vision and practical robotics.
Research Focus
Key Achievements
Top Papers
- 1