I am Peiliang Li, a third-year Ph.D student in HKUST UAV Group at the Robotics Institute of Hong Kong University of Science and Technology supervised by Prof. Shaojie Shen. During my first Ph.D year, I mainly focus on visual inertial
state estimation (VINS-Mono, VINS-Mobile) and its application (UAV navigation, Augmented Reality). After that I employ
the 3D geometry methods inspired from VINS to solve the 3D object and ego-motion tracking problem. I received my
B.Eng. degree in electrical science and technology from USTC, Hefei, China.
I'm interested in visual inertial fusion, 3D Computer Vision and Machine Learning with perticularlly looking for their combination to solve the 3D objects detection, tracking and ego-motion estimation for autonomous driving.
Contact : pliap at connect dot ust dot hk; peiliang.uav at gmail dot com
Wechat : mystery1221
[Scholar] [CV] [github]
Peiliang Li, Tong Qin, Shaojie Shen
European Conference on Computer Vision (ECCV 2018)
Stereo Vision-based Semantic 3D Object and Ego-motion Tracking for Autonomous Driving
VINS-Mono: A Robust and Versatile Monocular Visual-Inertial State Estimator
Tong Qin, Peiliang Li, Shaojie Shen
IEEE Transactions on Robotics (TRO 2018 Best Paper Honorable Mention)
Relocalization, Global Optimization, and Map Merging for Monocular Visual-Inertial SLAM
Tong Qin, Peiliang Li，Shaojie Shen
International Conference on Robotics and Automation (ICRA 2018)
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)
Peiliang Li, Xiaozhi Chen, Shaojie Shen
IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2019)
Stereo R-CNN based 3D Object Detection for Autonomous Driving
[Feb 2019] One paper accepted by CVPR 2019.
[Jan 2019] I will intern at Apple AI research team during 2019 summer.
[Apr 2019] Our journal paper VINS-Mono received the Honorable Mention for the 2018 IEEE T-RO Best Paper award!
[Apr 2019] The code of Stereo R-CNN is released here!