Xinxin Hu
Papers
2
Total Citations
61
H-Index
2
About
Xinxin Hu is a researcher advancing the field of autonomous perception through panoramic semantic segmentation. Her primary research areas include computer vision, deep learning, and surrounding sensing for autonomous transportation and robotics. Hu’s major contribution is the development of DS-PASS (Detail-Sensitive Panoramic Annular Semantic Segmentation), a novel pipeline that adapts state-of-the-art semantic segmentation to panoramic annular cameras, overcoming the limitations of narrow field-of-view pinhole cameras. Her 2020 paper on DS-PASS has garnered 53 citations, reflecting its impact on enabling comprehensive 360-degree scene understanding for self-driving vehicles and robotic systems. This work addresses a critical gap in perception systems, allowing for more robust and detailed interpretation of complex traffic environments. Hu’s research is notable for pushing the boundaries of semantic segmentation beyond conventional imaging, making her a key contributor to the evolution of autonomous navigation technologies.
Research Focus
Key Achievements
Top Papers
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- 2