Shaozu CAO | 曹绍祖
I am a PhD graduate of HKUST Aerial Robotics Group , supervised by Prof. Shaojie SHEN .
During PhD I mainly focused on high-precision and globally consistent SLAM with multiple low-cost sensors. By fusing the information from various low-cost and small-footprint sensors, I aim to design versatile, robust and accurate localization solutions for general spatial-aware applications.
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Research
I am interested in multi-sensor fusion SLAM, 3D perception, semantic-level scene modelling and understanding in real-world environments.
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GVINS: Tightly Coupled GNSS-Visual-Inertial Fusion for Smooth and Consistent State Estimation
Shaozu Cao ,
Xiuyuan Lu,
Shaojie Shen
IEEE Transactions on Robotics (TRO) , 2022
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GVINS significantly improves the global consistency of the visual-inertial odometry for long-range estimation.
VINS-Fusion: A General Optimization-based Framework for Global Pose Estimation with Multiple Sensors
Tong Qin,
Shaozu Cao ,
Jie Pan,
Peiliang Li,
Shaojie Shen
Arxiv , 2019
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VINS-Fusion achieves accurate localization for autonomous applications with multiple sensor modelities support.
A-LOAM: An Advanced Implementation of LOAM
Tong Qin,
Shaozu Cao ,
Shaojie Shen
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A-LOAM is an advanced implementation of LOAM (J. Zhang and S. Singh.), which greatly simplifies the code structure and provides an easy reference for SLAM researchers.
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RNNVis: Understanding Hidden Memories of Recurrent Neural Networks
Yao Ming,
Shaozu Cao ,
Ruixiang Zhang
Zhen Li
Yuanzhe Chen
Yangqiu Song
Huamin Qu
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RNNVis enables visual analytics on understanding and comparing recurrent neural networks (RNNs) for text-based applications.
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Last updated on February 2023
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