Zhixin Yan
Papers
1
Total Citations
14
H-Index
1
About
Zhixin Yan is a leading researcher in computer vision and 3D scene understanding, with a particular focus on omnidirectional depth estimation and immersive perception. Their most notable contribution is the development of **PanoDepth**, a pioneering two-stage framework for monocular omnidirectional depth estimation, introduced in their 2021 paper. This work addresses the critical challenge of extracting full 360-degree 3D information from a single image—a capability essential for applications in virtual reality, autonomous driving, and robotics. By proposing a model-agnostic pipeline that effectively handles the distortions inherent in panoramic imagery, Yan’s approach has set a new standard for accuracy and efficiency in the field. With 14 citations, this paper has already influenced subsequent research on spherical vision and depth completion. Yan’s work bridges the gap between traditional perspective-based methods and the demands of omnidirectional sensors, enabling more robust spatial reasoning in complex environments. Their research continues to push the boundaries of how machines perceive and interact with the world, making them a key figure in advancing next-generation immersive technologies.
Research Focus
Key Achievements
Top Papers
- 1