I am Qin Tong ( 秦通 ), a senior Ph.D. student in Aerial Robotics Group , Robotics Institute, with the Hong Kong University of Science and Technology (HKUST), Hong Kong. My supervisor is Shaojie SHEN . I received my B.Eng. degree in control science and engineering from Zhejiang University, Hangzhou, China, supervised by Chao XU .
Currently, I am a research intern in Facebook Reality Labs (Occulus Research), mentored by Anastasios Mourikis.
My research topics include SLAM, visual-inertial odometry(VIO), sensor fusion in autonomous robots and Augmented Reality.
- VINS-Mono: A Robust and Versatile Monocular Visual-Inertial State Estimator, Tong Qin, Peiliang Li, Shaojie Shen, IEEE Transactions on Robotics (T-RO 2018 Honorable Mention Best Paper) pdf video
- Autonomous Aerial Navigation Using Monocular Visual-Inertial Fusion, Yi Lin, Fei Gao, Tong Qin, Wenliang Gao, Tianbo Liu, William Wu, Zhenfei Yang, Shaojie Shen, Journal of Field Robotics (JFR) pdf video
- Online Temporal Calibration for Monocular Visual-Inertial Systems, Tong Qin, Shaojie Shen, International Conference on Intelligent Robots (IROS 2018 Best student paper) pdf
- Estimating Metric Poses of Dynamic Objects Using Monocular Visual-Inertial Fusion. Kejie Qiu, Tong QIN, Hongwen Xie, Shaojie Shen, International Conference on Intelligent Robots (IROS 2018) pdf
- Stereo Vision-based Semantic 3D Object and Ego-motion Tracking for Autonomous Driving, Peiliang Li, Tong Qin, Shaojie Shen, European Conference on Computer Vision (ECCV 2018) pdf video
- Relocalization, Global Optimization, and Map Merging for Monocular Visual-Inertial SLAM, Tong Qin, Shaojie Shen, International Conference on Robotics and Automation (ICRA 2018) pdf video
- Robust Initialization of Monocular Visual-Inertial Estimation on Aerial Robots, Tong Qin, Shaojie Shen, International Conference on Intelligent Robots (IROS 2017) pdf video
- Monocular Visual-Inertial State Estimation for Mobile Augmented Reality, Peiliang Li, Tong Qin, Botao Hu, Fengyuan Zhu, Shaojie Shen, International Symposium on Mixed and Augmented Reality (ISMAR 2017) pdf video