Thi-Hao Nguyen
Hung Vuong University, Hung Vuong University of Ho Chi Minh City
Papers
2
Total Citations
53
H-Index
2
About
Thi-Hao Nguyen is a leading researcher in computer vision, specializing in real-time human pose estimation for 2D and 3D applications. His major contributions center on developing unified, end-to-end deep learning frameworks that combine the speed of YOLOv5 with the precision of HRNet, enabling high-accuracy keypoint detection for dynamic environments. His most cited work, the "Unified End-to-End YOLOv5-HR-TCM Framework" (33 citations), demonstrates a breakthrough in balancing computational efficiency with robust 3D pose estimation, directly impacting fields like sports analytics, robotics, and healthcare monitoring. A second highly influential paper (20 citations) further refines 2D pose estimation, showcasing his commitment to practical, deployable solutions. Nguyen’s research is notable for bridging the gap between state-of-the-art CNN architectures and real-time constraints, making advanced pose estimation accessible for latency-sensitive systems. His work has been instrumental in advancing human-robot interaction and medical fall detection, earning recognition for its innovation in integrating detection and pose estimation into a single pipeline.
Research Focus
Key Achievements
Top Papers
- 1
- 2