Jinxin Xu
Papers
1
Total Citations
7
H-Index
1
About
Dr. Jinxin Xu has made significant contributions to the field of computer vision, with a primary focus on stereo matching—a critical technology underpinning 3D reconstruction, autonomous navigation, and industrial measurement. Their most cited work, "Stereo matching using census cost over cross window and segmentation-based disparity refinement" (2018, 7 citations), introduces a novel approach that enhances the accuracy and practicality of depth estimation. By combining a census transform cost over an adaptive cross-shaped window with segmentation-based refinement, Dr. Xu’s method effectively handles challenging regions like object boundaries and textureless areas, improving disparity map quality. This work addresses key limitations in traditional stereo algorithms, offering a robust solution for real-world applications. Dr. Xu’s research demonstrates a commitment to advancing 3D vision technologies, with their method serving as a valuable reference for subsequent studies in robotic perception and scene understanding. Their contributions continue to influence the development of more reliable and efficient stereo matching systems.
Research Focus
Key Achievements
Top Papers
- 1