Xiaojin Gong

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About

Xiaojin Gong is a prominent researcher in computer vision and robotics, with a focus on 3D perception and sensor fusion. Her most-cited work, "Extrinsic calibration of a 3D LIDAR and a camera using a trihedron" (2012), has garnered 31 citations, establishing a foundational method for aligning LiDAR and camera data in autonomous systems. This contribution is critical for enabling accurate environmental mapping and object detection in self-driving cars and robotics. Gong’s research spans multi-modal sensor integration, 3D reconstruction, and visual tracking, often emphasizing practical, real-world applications. Her calibration technique, which uses a simple trihedron target, simplifies the complex process of extrinsic calibration, making it accessible for both academic and industrial use. Beyond this, she has advanced work in point cloud processing and depth estimation, with her papers collectively cited hundreds of times, reflecting their impact on the field. Gong’s achievements include collaborations on autonomous vehicle projects and contributions to top-tier conferences, solidifying her reputation as a key figure in bridging the gap between 2D and 3D vision systems. Her work continues to inspire students and researchers tackling sensor fusion challenges.