Geehyuk Lee — accepted AI-conference papers

2026

Real-Time Multimodal Fingertip Contact Detection via Depth and Motion Fusion for Vision-Based Human-Computer Interaction

Mukhiddin Toshpulatov, Wookey Lee, Suan Lee, Geehyuk Lee

CVPR 2026

Precise fingertip contact detection is a fundamental challenge for natural and immersive virtual reality (VR) interaction. However, existing vision-based methods suffer from insufficient accuracy, with typical depth errors (12-25 mm) being too large to reliably distinguish between hovering and true

Cited by 0 Source ↗Scholar ↗

2019

Robots Learn Social Skills: End-to-End Learning of Co-Speech Gesture Generation for Humanoid Robots

Youngwoo Yoon, Woo-Ri Ko, Minsu Jang, Jaeyeon Lee, Jaehong Kim, Geehyuk Lee

ICRA 2019poster

Co-speech gestures enhance interaction experiences between humans as well as between humans and robots. Most existing robots use rule-based speech-gesture association, but this requires human labor and prior knowledge of experts to be implemented. We present a learning-based co-speech gesture genera…

Cited by 301 Source ↗Scholar ↗