Rui Wang

Rui Wang (王锐)

I am a Senior Research Scientist at the Microsoft Mixed Reality & AI Lab in Zurich. Before joining Microsoft, I pursued my PhD in Computer Science in the Chair of Computer Vision & Artificial Intelligence at TUM, where I was advised by Prof. Daniel Cremers. In 2018, I did an internship in the Nvidia Robotics Research Lab in Seattle, supervised by Prof. Dieter Fox. In parallel with pursuing my PhD, I also worked as a Senior Computer Vision Researcher at Artisense, a startup co-founded by Prof. Cremers. I received my Master from TUM and my Bachelor from Xi'an Jiaotong University.

My research interests include visual odometry, SLAM, visual 3D reconstruction, as well as their combinations with semantic information. More broadly, I am interested in computer vision and machine learning.

If you are interested in these topics, feel free to reach out for internship and thesis opportunities.

Email / Google Scholar / LinkedIn / GitHub / Homepage@TUM

News

[04/2024]	We have two papers accepted by CVPR, one by ICRA, one by RA-L. Congrats to the co-authors.
[03/2021]	I join the Microsoft Mixed Reality & AI Lab Zurich as a Senior Research Scientist.
[05/2020]	We are organizing a workshop with a challenge on Map-based Localization for Autonomous Driving at ECCV 2020.
[05/2018]	I will be interning with Dieter Fox in the Nvidia Robotics Research Lab in Seattle.
[03/2018]	I join Artisense as a Senior Computer Vision Researcher and continue my PhD there.

Education

	Technical University of Munich PhD Computer Science 2016-2020
	Technical University of Munich Master Electrical Engineering and Information Technology 2011-2014
	Xi'an Jiaotong University Bachelor Automation 2007-2011

Highlight Videos

Publications

	A Spatiotemporal Hand-Eye Calibration for Trajectory Alignment in Visual(-Inertial) Odometry Evaluation Zichao Shu, Lijun Li, Rui Wang, Zetao Chen RA-L, 2024 paper
	F³Loc: Fusion and Filtering for Floorplan Localization Changan Chen, Rui Wang, Christoph Vogel, Marc Pollefeys CVPR, 2024 (Highlight) paper \| project page \| code \| dataset
	LEAP-VO: Long-term Effective Any Point Tracking for Visual Odometry Weirong Chen, Le Chen, Rui Wang, Marc Pollefeys CVPR, 2024 paper \| project page
	Leveraging Neural Radiance Fields for Uncertainty-Aware Visual Localization Le Chen, Weirong Chen, Rui Wang, Marc Pollefeys ICRA, 2024 paper \| video
	CASSPR: Cross Attention Single Scan Place Recognition Yan Xia, Mariia Gladkova, Rui Wang, Qianyun Li, Uwe Stilla, Joao F Henriques, Daniel Cremers ICCV, 2023 paper \| code
	SOE-Net: A Self-Attention and Orientation Encoding Network for Point Cloud based Place Recognition Yan Xia, Yusheng Xu, Shuang Li, Rui Wang, Juan Du, Daniel Cremers, Uwe Stilla CVPR, 2021 (Oral Presentation) paper \| code
	Tight Integration of Feature-based Relocalization in Monocular Direct Visual Odometry Mariia Gladkova, Rui Wang, Niclas Zeller, Daniel Cremers ICRA, 2021 paper \| project page \| video \| teaser video
	4Seasons: A Cross-Season Dataset for Multi-Weather SLAM in Autonomous Driving Patrick Wenzel, Rui Wang, Nan Yang, Qing Cheng, Qadeer Khan,Lukas von Stumberg, Niclas Zeller, Daniel Cremers GCPR, 2020 paper \| project page \| dataset \| video
	Learning Monocular 3D Vehicle Detection without 3D Bounding Box Labels Lukas Koestler, Nan Yang, Rui Wang, Daniel Cremers GCPR, 2020 paper \| supplement \| project page \| data \| video \| teaser video
	DH3D: Deep Hierarchical 3D Descriptors for Robust Large-Scale 6DoF Relocalization Juan Du^, Rui Wang^, Daniel Cremers ECCV, 2020 (^equal contribution) (Spotlight Presentation)* paper \| supplement \| project page \| code \| data \| video \| teaser video
	D3VO: Deep Depth, Deep Pose and Deep Uncertainty for Monocular Visual Odometry Nan Yang, Lukas von Stumberg, Rui Wang, Daniel Cremers CVPR, 2020 (Oral Presentation) paper & supplement \| project page \| video
	DirectShape: Photometric Alignment of Shape Priors for Visual Vehicle Pose and Shape Estimation Rui Wang, Nan Yang, Joerg Stueckler, Daniel Cremers ICRA, 2020 paper \| supplement \| project page \| video \| presentation
	Deep Virtual Stereo Odometry: Leveraging Deep Depth Prediction for Monocular Direct Sparse Odometry Nan Yang, Rui Wang, Joerg Stueckler, Daniel Cremers ECCV, 2020 (Oral Presentation) paper \| supplement \| project page \| video \| presentation
	Challenges in Monocular Visual Odometry: Photometric Calibration, Motion Bias and Rolling Shutter Effect Nan Yang^, Rui Wang^, Xiang Gao, Daniel Cremers RA-L and IROS, 2018 (^*equal contribution) paper
	LDSO: Direct Sparse Odometry with Loop Closure Xiang Gao, Rui Wang, Nikolaus Demmel, Daniel Cremers IROS, 2018 paper \| project page \| video \| code
	Online Photometric Calibration of Auto Exposure Video for Realtime Visual Odometry and SLAM Paul Bergmann, Rui Wang, Daniel Cremers RA-L and ICRA, 2018 (Best Vision Paper Award - Finalist) paper \| project page \| video \| code
	Stereo DSO: Large-Scale Direct Sparse Visual Odometry with Stereo Cameras Rui Wang^, Martin Schwoerer^, Daniel Cremers ICCV, 2017 (^*equal contribution) paper \| supplement \| project page \| video (VO) \| video (SLAM)