Chi Su

Papers

1

Total Citations

2

H-Index

1

About

Chi Su is a leading researcher in intelligent robotic vision and urban infrastructure inspection, with a focus on 3D reconstruction and depth prediction for sewer systems. His most-cited work, "Pipeline Inner Surface 3D Reconstruction and Depth Prediction Based on Fast-MVSNet for Intelligent Sewer Robot Vision" (2023), addresses a critical gap in urban drainage maintenance: the reliance on monocular CCTV videos that provide only 2D images without spatial localization. By integrating Fast-MVSNet with robotic vision, Su developed a method to generate accurate 3D models and depth maps of pipeline interiors, enabling robots to autonomously navigate and assess structural conditions. This contribution has significant implications for smart city management, reducing the need for manual inspection and improving the efficiency of infrastructure maintenance. With 2 citations in its early publication stage, the work is gaining traction among researchers in robotics and civil engineering. Su’s research bridges computer vision and practical urban engineering, offering scalable solutions for aging drainage systems worldwide. His innovative approach positions him as a key figure in advancing intelligent sewer inspection technologies.

Research Focus

Key Achievements

1
H-Index
1
Papers
2
Total Citations
2
Avg Citations/Paper
🏆 Most Cited Paper
Pipeline Inner Surface 3D Reconstruction and Depth Prediction Based on Fast-MVSNet for Intelligent Sewer Robot Vision
2 citations · 2023
📈 Most Prolific Year: 2023 (1 Papers)
🤝 Key Collaborators: 5

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago