Jinghui Guo
Papers
1
Total Citations
6
H-Index
1
About
Jinghui Guo is a computer vision researcher whose work focuses on 3D reconstruction from limited data, with particular emphasis on point cloud generation—a critical capability for robotics, autonomous vehicles, and augmented reality. In their highly cited 2021 paper "Generating Point Cloud from Single Image in The Few Shot Scenario," Guo tackles one of the field's most challenging problems: reconstructing accurate 3D point clouds from just a single 2D image when training data is scarce. This work bridges the gap between deep learning's data hunger and real-world applications where labeled 3D data is expensive to obtain. By developing frameworks that perform robustly even in few-shot settings, Guo's research pushes the boundaries of practical 3D vision systems. Their contributions are particularly valuable for scenarios where traditional multi-view or depth-sensor approaches are infeasible. With 6 citations on this foundational paper, Guo's work is gaining traction among researchers seeking to make 3D reconstruction more accessible and data-efficient. Their research represents an important step toward deploying advanced computer vision in resource-constrained environments.
Research Focus
Key Achievements
Top Papers
- 1Generating Point Cloud from Single Image in The Few Shot Scenario6 citations · 2021