Seongbo Ha

Papers

Total Citations

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About

Seongbo Ha is a rising researcher in robotics and computer vision, whose work centers on advancing dense Simultaneous Localization and Mapping (SLAM) for real-world applications in robotics, Virtual Reality (VR), and Augmented Reality (AR). His most impactful contribution, "RGBD GS-ICP SLAM" (2024), has already garnered over 50 citations, reflecting its significance in the field. This work pioneers the integration of 3D Gaussian representations with the Iterative Closest Point (ICP) algorithm, enabling highly accurate, real-time dense mapping from RGB-D data. By leveraging neural scene representation and 3D Gaussians, Ha’s approach overcomes traditional limitations in SLAM, offering robust performance in dynamic environments and enhancing spatial understanding for autonomous systems. His research bridges the gap between efficient geometric registration and photorealistic scene reconstruction, a critical step toward immersive VR/AR experiences and reliable robotic navigation. As an early-career scholar, Ha’s rapid citation impact signals his growing influence, positioning him as a key innovator in dense SLAM. His work not only pushes the boundaries of real-time mapping but also provides a practical foundation for next-generation spatial intelligence in robotics and mixed reality.