Papers
1
Total Citations
3
H-Index
1
About
Xi Xu is a researcher focused on advancing computer vision for autonomous systems, particularly in the challenging domain of fisheye object detection. Her key contribution lies in addressing the scarcity of large-scale fisheye datasets by developing innovative strategies that leverage standard image datasets. In her notable 2022 work, she proposed a 24-points regression strategy that enables models trained on conventional images to effectively detect objects in distorted fisheye views—a critical capability for robotics and autonomous driving. This approach bridges a significant gap in real-world perception, where wide-angle cameras are essential but data-hungry. While her citation count is still growing, her work represents a practical and resourceful solution to a pressing problem in the field. By reducing reliance on specialized fisheye datasets, Xu’s research offers a scalable path to improving object detection in complex environments, making her a promising voice in the intersection of data efficiency and robust visual perception.
Research Focus
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Top Papers
- 1