Yufei Zhao
Papers
1
Total Citations
2
H-Index
1
About
Yufei Zhao is a leading researcher in computer vision and 3D scene understanding, with a particular focus on indoor spatial geometry estimation. His most-cited work, a comprehensive survey on 3D indoor scene geometry estimation from a single omnidirectional image, provides a critical synthesis of techniques that extract structural information from 360° panoramic data. This survey has already garnered early citations, highlighting its importance in enabling immersive applications such as virtual reality, robotics navigation, and augmented reality. Zhao’s contributions center on transforming complex omnidirectional imagery into accurate 3D models of indoor environments—a challenging problem that bridges computer vision and geometry. By systematically reviewing methods for depth estimation, layout prediction, and surface reconstruction from a single viewpoint, his work offers a foundational resource for researchers tackling scene understanding. His research is particularly impactful for advancing autonomous systems that must interpret cluttered, real-world interiors. With a growing citation footprint, Zhao is establishing himself as a key voice in the field, and his survey serves as an essential reference for anyone working on 3D reconstruction from unconventional camera inputs.
Research Focus
Key Achievements
Top Papers
- 1