Bing WANG
Biography
I’m a D.Phil student at the Department of Computer Science, University of Oxford. My research interests broadly lie in Robotics and Computer Vision. In particular, my research concentrates on the design of intelligent perception solutions for autonomous systems, and the development of reliable 3D scene understanding algorithms on mobile robotics operating in the real world. I work in Cyber Physical Systems Group under the supervision of Prof. Niki Trigoni and Prof. Andrew Markham. If you have interests in my research or would like to work with me, welcome to drop me an email (bingw218@gmail.com) for discussion.
Selected Publications
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PointLoc: Deep Pose Regressor for LiDAR Point Cloud Localization
Wei Wang‚ Bing Wang‚ Peijun Zhao‚ Changhao Chen‚ Ronald Clark‚ Bo Yang‚ Andrew Markham and Niki Trigoni
In IEEE Sensors Journal. 2021.
Details about PointLoc: Deep Pose Regressor for LiDAR Point Cloud Localization | BibTeX data for PointLoc: Deep Pose Regressor for LiDAR Point Cloud Localization | Download (pdf) of PointLoc: Deep Pose Regressor for LiDAR Point Cloud Localization
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3D Motion Capture of an Unmodified Drone with Single−Chip Millimeter Wave Radar
N. Trigoni Z.Peijun C.X. Lu B. Wang and A. Markham
In IEEE International Conference on Robotics and Automation (ICRA). 2021.
Details about 3D Motion Capture of an Unmodified Drone with Single−Chip Millimeter Wave Radar | BibTeX data for 3D Motion Capture of an Unmodified Drone with Single−Chip Millimeter Wave Radar | Download (pdf) of 3D Motion Capture of an Unmodified Drone with Single−Chip Millimeter Wave Radar
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VMLoc: Variational Fusion For Learning−Based Multimodal Camera Localization
Kaichen Zhou Changhao Chen Bing Wang Muhamad Risqi U. Saputra Niki Trigoni and Andrew Markham
In AAAI Conference on Artificial Intelligence (AAAI). 2021.
Details about VMLoc: Variational Fusion For Learning−Based Multimodal Camera Localization | BibTeX data for VMLoc: Variational Fusion For Learning−Based Multimodal Camera Localization | Download (pdf) of VMLoc: Variational Fusion For Learning−Based Multimodal Camera Localization