Xubo Luo is a first-year graduate student at University of Chinese Academy of Sciences, advised by Prof.Wan. Previously, he obtained his Bachelor’s degree from Shanghai University of Finance and Economy, advised by Prof.Kwok. His research area includes visual localization, machine vision and SLAM. More detailed information can be found HERE.

News

  • 2022.12: One paper is accpeted by ICoSR 2022!
  • 2023.06: Graduate with honors from SUFE!

Publications

UAV Localization

ICoSR2022
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Deep learning based cross-view image matching for UAV geo-localization.
Xubo Luo, Yaolin Tian, Xue Wan, Jinzhong Xu, Tao Ke

  • Due to the large scale and illumination difference between aerial and satellite images, it is challenging that most existing cross-view image matching algorithms fail to localize the UAV robustly and accurately. To solve the above problem, a novel UAV localization framework containing three-stage coarse-to-fine image matching is proposed.
  • Paper Project
IROS2024
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JointLoc: A Real-time Visual Localization Framework for Planetary UAVs Based on Joint Relative and Absolute Pose Estimation. (Under Review)
Xubo Luo, Xue Wan, Yixing Gao, Yaolin Tian, Wei Zhang, Leizheng Shu

  • In order to accurately determine the position of the UAV in a planetary scene in the absence of the global navigation satellite system (GNSS), this paper proposes JointLoc, which estimates the real-time UAV position in the world coordinate system by adaptively fusing the absolute 2-degree-of-freedom (2-DoF) pose and the relative 6-degree-of-freedom (6-DoF) pose.
  • Paper Project

Image Fusion

CVIU
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HBANet: A hybrid boundary-aware attention network for infrared and visible image fusion. (Under Review)
Xubo Luo, Liping Wang, Jinshuo Zhang, Dongmei Niu

  • In this article, we propose a novel image fusion approach based on hybrid boundary-aware attention, termed HBANet, which models global dependencies across the image and leverages boundary-wise prior knowledge to supplement local details. Specifically, we design a novel mixed boundary-aware attention module that is capable of leveraging spatial information to the fullest extent and integrating long dependencies across different domains.
  • Paper Project

Honors and Awards

  • 2021.10 People’s Scholarship, Shanghai University of Finance and Economics
  • 2023.06 Honor Graduate, Shanghai University of Financeand Economics

Educations

  • 2023.09 - 2026.06 (Expected), Master, University of Chinese Academy of Sciences, Beijing.
  • 2019.09 - 2023.06, Bachelor, Shanghai University of Finance and Economics, Shanghai.

Internships

  • 2023.02 - 2023.08, Technology and Engineering Center for Space Utilization, Chinese Academy of Sciences

Services

Paper Reviewer

  • 2023.09 - 2023.10, IEEE Robotics and Automation Letters (RAL)