About

I am Hu Xue, with the School of Computer Science and Technology at Chongqing University of Post and Telecommunications, Chongqing, China. My research focuses on multimodal perception, deep learning, sensor fusion, and robust positioning, with applications in RGB-T visual tracking and vision-aided GNSS positioning.

My recent work explores how complementary sensing modalities can be fused more effectively in challenging real-world environments. In visual tracking, I study lightweight and parameter-efficient fusion methods for visible-thermal infrared tracking. In positioning, I work on integrating sky-pointing fisheye imagery with GNSS observations to improve localization accuracy in urban canyons.

Research Interests

• Multimodal learning and feature fusion
• Visible-thermal infrared object tracking
• Vision-aided GNSS positioning
• Parameter-efficient deep learning
• Robust perception in complex environments

Recent Publications

• “Feature Fusion and Enhancement for Lightweight Visible-Thermal Infrared Tracking via Multiple Adapters,” IEEE Transactions on Circuits and Systems for Video Technology.
• “VGPNet: A Vision-aided GNSS Positioning Framework with Cross-Channel Feature Fusion for Urban Canyons,” IEEE Transactions on Instrumentation and Measurement.