Hongkai Yu

Papers

Total Citations

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About

Hongkai Yu is a researcher whose work bridges the frontiers of computer vision and assistive robotics. His primary research areas include self-supervised monocular depth estimation and human-robot interaction for healthcare applications. Yu’s most significant contribution is the development of **SQLdepth**, a novel framework for generalizable self-supervised fine-structured monocular depth estimation. Published in 2024, this work has already garnered **51 citations**, highlighting its rapid impact. By moving beyond immediate visual features to recover fine-grained scene details, SQLdepth addresses a critical limitation in existing depth estimation methods, with direct applications in autonomous driving and robotics. In parallel, Yu has made notable contributions to assistive technology, co-authoring a **2022 proof-of-concept study** on a hands-free interface for robot-assisted self-feeding. This system, designed for individuals with movement disorders, demonstrates his commitment to translating computer vision research into tangible societal benefits. Through his work, Yu is advancing both the theoretical foundations of self-supervised learning and the practical development of autonomous systems that can perceive and interact with the world in a more nuanced, human-centered manner.