Hyung-Il Kim

Electronics and Telecommunications Research Institute

Papers

Total Citations

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About

Hyung-Il Kim is a leading researcher in computer vision, with a primary focus on robust object detection for safety-critical applications. His work addresses a fundamental challenge: enabling object detectors to reliably operate in unstable, real-world environments plagued by sensor noise and incomplete data. Kim’s major contribution is pioneering the estimation of localization uncertainty in anchor-free object detection, a paradigm shift from traditional methods that treat detection as deterministic. By explicitly modeling where and how much a detector might be uncertain, his approach enhances reliability for systems like surgical robots and autonomous vehicles. His foundational 2020 paper on this topic has accumulated significant citations, and its 2023 extension continues to shape the field. Kim’s research bridges the gap between theoretical robustness and practical deployment, making him a key figure in advancing trustworthy AI for high-stakes domains. His work not only improves detection accuracy but also provides critical confidence metrics, empowering downstream systems to make safer decisions.