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 Daniel Cremers. In 2018, I did an internship in the Nvidia Robotics Research Lab in Seattle, supervised by Dieter Fox. In parallel with doing my PhD, I also worked as a Senior Computer Vision Researcher at Artisense, a startup co-founded by Daniel. 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

profile photo
News
[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
blind-date Technical University of Munich
PhD
Computer Science
2016-2020
blind-date Technical University of Munich
Master
Electrical Engineering and Information Technology
2011-2014
blind-date Xi'an Jiaotong University
Bachelor
Automation
2007-2011
Highlight Videos
Publications
fast-texture 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
fast-texture 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
fast-texture 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
fast-texture 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
fast-texture 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 | data | video | teaser video
fast-texture 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
fast-texture 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
fast-texture 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
fast-texture 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
fast-texture LDSO: Direct Sparse Odometry with Loop Closure
Xiang Gao, Rui Wang, Nikolaus Demmel, Daniel Cremers
IROS, 2018
paper | project page | video | code
fast-texture 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
fast-texture 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)
Academic Services

Conference reviewer
CVPR, ICCV, ECCV, ICRA, IROS, AAAI

Journal reviewer
RA-L, T-RO, AURO, TMM, P&RS, Pattern Recognition, IJRR

Organizer
ECCV 2020 Workshop on Map-based Localization for Autonomous Driving


Created based on Jon Barron's code.

Last updated: March 8, 2022