Zhengyan Tang
Papers
1
Total Citations
2
H-Index
1
About
Zhengyan Tang is a researcher at the forefront of intelligent infrastructure inspection, specializing in computer vision, 3D reconstruction, and robotic perception for urban drainage systems. Their major contribution lies in advancing sewer robot vision by developing methods to transform traditional 2D CCTV pipe inspections into accurate 3D reconstructions. In their notable 2023 work, "Pipeline Inner Surface 3D Reconstruction and Depth Prediction Based on Fast-MVSNet for Intelligent Sewer Robot Vision," Tang pioneered a deep learning approach that enables robots to perceive depth and spatial geometry within confined, dark pipe environments—a critical step toward automated, non-destructive infrastructure assessment. This research directly addresses the limitations of monocular video, which lacks localization data, by providing actionable 3D maps for maintenance crews. With 2 citations and growing recognition, Tang’s work is foundational for smart city applications, reducing manual inspection risks and improving drainage system reliability. Their achievements demonstrate a powerful blend of applied AI and civil engineering, positioning them as an emerging leader in robotic vision for critical urban infrastructure.
Research Focus
Key Achievements
Top Papers
- 1