Young-Woon Cha
Papers
2
Total Citations
6
H-Index
2
About
Young-Woon Cha is a rising researcher at the intersection of robotics, computer vision, and extended reality (XR), with a primary focus on enabling seamless human–robot interaction through advanced pose estimation. His work addresses a critical bottleneck in telepresence and digital human systems: the lack of accurate, full-body pose data for diverse humanoid robots. In his 2024 paper on *Diverse Humanoid Robot Pose Estimation from Images Using Only Sparse Datasets*, Cha introduces a novel dataset and methodology that overcomes the scarcity of large-scale training data, achieving robust pose estimation across varied robot morphologies—a key enabler for immersive XR applications. Complementing this, his work on *Full-Body Pose Estimation of Humanoid Robots Using Head-Worn Cameras* pioneers a telepresence system that maps a remote user’s movements onto a robot’s body, allowing for realistic, embodied communication. Though early in his career, with each paper garnering 3 citations, Cha’s contributions are foundational, directly tackling the realism gap in robotic teleoperation. His research promises to transform how we interact with remote environments, making digital human-augmented telepresence both physically and visually authentic.
Research Focus
Key Achievements
Top Papers
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- 2