Shaohui Jiao

Papers

1

Total Citations

51

H-Index

1

About

Shaohui Jiao is a leading researcher in computer vision and autonomous systems, with a primary focus on self-supervised monocular depth estimation—a critical technology for enabling perception in autonomous driving and robotics. His most impactful contribution is the development of SQLdepth, a novel framework introduced in 2024 that achieves generalizable, fine-structured depth estimation without requiring labeled data. This work directly addresses a longstanding limitation in the field: the inability of conventional self-supervised methods to recover intricate scene details from monocular inputs. By leveraging structured query learning, SQLdepth significantly improves depth granularity and cross-scene generalization, garnering 51 citations in its first year and establishing Jiao as a rising authority in the domain. His research bridges the gap between theoretical depth estimation and practical deployment, offering robust solutions for real-world environments where fine-grained spatial understanding is essential. Jiao’s work is widely cited by researchers advancing autonomous navigation and 3D scene understanding, and his innovative approach to self-supervised learning continues to influence next-generation perception systems.

Research Focus

Key Achievements

1
H-Index
1
Papers
51
Total Citations
51
Avg Citations/Paper
🏆 Most Cited Paper
SQLdepth: Generalizable Self-Supervised Fine-Structured Monocular Depth Estimation
51 citations · 2024
📈 Most Prolific Year: 2024 (1 Papers)
🤝 Key Collaborators: 4

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 11 days ago