Meiyu Huang
Papers
1
Total Citations
23
H-Index
1
About
Dr. Meiyu Huang is a rising leader in computational imaging, with a primary focus on non-line-of-sight (NLOS) recognition—a technique that reveals hidden objects beyond the direct line of sight. Her most-cited work, "Accurate but fragile passive non-line-of-sight recognition" (2021, 23 citations), makes a pivotal contribution by demonstrating that passive NLOS recognition, while highly accurate, is surprisingly sensitive to subtle environmental changes. This finding challenges the robustness of current deep learning approaches and provides a critical roadmap for developing more reliable systems for autonomous vehicles and robotic vision. By systematically analyzing the fragility of these models, Dr. Huang’s research bridges the gap between high-performance algorithms and real-world deployment, where conditions are unpredictable. Her work has already influenced subsequent studies in the field, establishing a foundation for more resilient passive sensing technologies. For students and researchers, Dr. Huang exemplifies how careful experimental analysis can reveal hidden vulnerabilities in state-of-the-art methods, driving the field toward more practical and trustworthy solutions for seeing around corners.
Research Focus
Key Achievements
Top Papers
- 1Accurate but fragile passive non-line-of-sight recognition23 citations · 2021