Zihao Sheng
Papers
1
Total Citations
25
H-Index
1
About
Zihao Sheng is a researcher advancing the field of computer vision, with a primary focus on real-time 6D object pose estimation—a critical technology for applications in robotic manipulation, augmented reality, and autonomous systems. His most cited work, "HRPose: Real-Time High-Resolution 6D Pose Estimation Network Using Knowledge Distillation" (2023, 25 citations), introduces a lightweight yet highly accurate model that leverages knowledge distillation to achieve high-resolution pose estimation from RGB images in real-time. This contribution addresses a key challenge in the field: balancing computational efficiency with precision, enabling practical deployment in resource-constrained environments. Sheng’s approach not only improves inference speed but also maintains robust performance, making it suitable for dynamic, real-world scenarios. By focusing on model compression and high-resolution feature extraction, his work has garnered attention from both academia and industry, with citations reflecting its growing influence. Sheng’s research continues to push the boundaries of efficient vision systems, offering scalable solutions that bridge the gap between theoretical advances and practical robotics and AR applications.
Research Focus
Key Achievements
Top Papers
- 1