Xiaorui Qiao

The University of Tokyo

Papers

2

Total Citations

11

H-Index

2

About

Xiaorui Qiao is a researcher specializing in underwater computer vision and robotics, with a focus on overcoming the unique challenges of imaging in aquatic environments. Her work addresses two critical barriers to autonomous underwater operation: severe image degradation caused by light absorption and scattering, and the geometric distortions introduced by refraction. In her highly cited 2018 paper, Qiao proposed an improved underwater light model and a novel enhancement algorithm that dramatically improves visibility for underwater robots, directly enabling more reliable inspection and detection tasks. Her 2019 contribution tackles the complex problem of Structure from Motion (SfM) in underwater scenes, developing a method that simultaneously corrects for both image degradation and refractive effects to produce accurate 3D reconstructions. While her citation counts reflect the specialized nature of her field, Qiao’s work is foundational for advancing autonomous underwater vehicles in murky, challenging environments. Her dual focus on image restoration and geometric accuracy positions her as a key contributor to making underwater robots more capable for scientific exploration, infrastructure inspection, and environmental monitoring.

Research Focus

Key Achievements

2
H-Index
2
Papers
11
Total Citations
6
Avg Citations/Paper
🏆 Most Cited Paper
Visibility Enhancement for Underwater Robots Based on an Improved Underwater Light Model
7 citations · 2018
📈 Most Prolific Year: 2018 (1 Papers)
🤝 Key Collaborators: 4
🏛 Institutions: The University of Tokyo

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago