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members:wangr [2019/04/25 20:50] Rui Wang |
members:wangr [2020/05/28 12:47] Rui Wang |
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==== News ==== | ==== News ==== |
* [10.2018] The code for LDSO (Direct Sparse Odometry with Loop Closure) has been released! Please visit the [[https://vision.in.tum.de/research/vslam/ldso|project page]] for details. | * [05.2020] We are organizing a workshop together with a challenge on [[https://sites.google.com/view/mlad-eccv2020|Map-based Localization for Autonomous Driving]] at ECCV 2020, Glasgow, UK. |
| * [05.2020] The results of Stereo DSO on KITTI Odometry test set are uploaded to the [[https://vision.in.tum.de/research/vslam/stereo-dso|project page]]. |
| * [02.2020] D3VO is accepted by CVPR 2020.([[https://arxiv.org/abs/2003.01060|arxiv]]) |
| * [01.2020] DirectShape has been accepted by ICRA 2020. It is an optimization pipeline that estimates the 3D poses and shapes of cars directly from a stereo image pair, no 3D points are needed. ([[https://vision.in.tum.de/research/vslam/direct-shape|project page]]) |
| * [10.2018] The code for LDSO (Direct Sparse Odometry with Loop Closure) has been released! ([[https://vision.in.tum.de/research/vslam/ldso|project page]]). |
* [07.2018] We have one paper accepted by ECCV'18 (oral) and two papers accepted by IROS'18. | * [07.2018] We have one paper accepted by ECCV'18 (oral) and two papers accepted by IROS'18. |
* [06-12.2018] I will be interning with Prof. Dieter Fox in the recently founded Nvidia Robotics Research Lab in Seattle. | * [06-12.2018] I will be interning with Prof. Dieter Fox in the Nvidia Robotics Research Lab in Seattle. |
* [05.2018] We have released our code for Online Photometric Calibration! Please find the link on the [[https://vision.in.tum.de/research/vslam/photometric-calibration|project page]]. The paper was recently nominated by ICRA'18 for the Best Vision Paper Award. | * [05.2018] We have released our code for Online Photometric Calibration! Please find the link on the [[https://vision.in.tum.de/research/vslam/photometric-calibration|project page]]. The paper was recently nominated by ICRA'18 for the Best Vision Paper Award. |
* [03.2018] I join [[https://www.artisense.ai/|Artisense]], a startup co-founded by Prof. Daniel Cremers, as a PhD Student and Senior Computer Vision & AI Researcher. | |
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==== Brief Bio ==== | ==== Brief Bio ==== |
I received my Bachelor's degree (2011) in Automation from Xi'an Jiaotong University, and my Master's degree (2014) in Electrical Engineering and Information Technology from the Technical University of Munich. | I received my Bachelor's degree (2011) in Automation from Xi'an Jiaotong University, and my Master's degree (2014) in Electrical Engineering and Information Technology from the Technical University of Munich. |
From 2014 to 2016 I worked as a computer vision algorithm developer for advanced driver assistance systems (ADAS) at Continental. Since March 2016 I am a PhD student in the Computer Vision Group at the Technical University of Munich, headed by Professor **Daniel Cremers**. My research interests include visual SLAM and visual 3D reconstruction, as well as their combinations with semantic information. | From 2014 to 2016 I worked as a computer vision algorithm developer for advanced driver assistance systems (ADAS) at Continental. Since March 2016 I am a PhD student in the Computer Vision Group at the Technical University of Munich, headed by Professor Daniel Cremers. In 2018 I joined [[https://www.artisense.ai/|Artisense]], a startup co-founded by Professor Cremers, as a PhD student and senior computer vision & AI researcher. My research interests include visual SLAM and visual 3D reconstruction, as well as their combinations with semantic information. I am planning to finish my PhD in 2020. |
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Find me on [[https://scholar.google.de/citations?user=buN3yw8AAAAJ&hl=en|Google Scholar]], | Find me on [[https://scholar.google.de/citations?user=buN3yw8AAAAJ&hl=en|Google Scholar]], |
[[https://www.linkedin.com/in/rui-wang-5367398a|LinkedIn]], [[https://www.strava.com/athletes/22551758|Strava]]. | [[https://www.linkedin.com/in/rui-wang-5367398a|LinkedIn]], [[https://www.strava.com/athletes/22551758|Strava]] (highly research related). |
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==== Research Interests ==== | ==== Research Interests ==== |
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=== Visual Odometry / SLAM === | === Semantic VO / SLAM === |
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| * ** DirectShape ** This video shows the basic idea and some results of our paper "DirectShape: Photometric Alignment of Shape Priors for Visual Vehicle Pose and Shape Estimation". In this work, we estimate the 3D poses and shapes of cars based on a single stereo image pair. ** Note that the point clouds in the video are only for visualization purpose, they are not used in our method. ** For more details please refer to the [[https://vision.in.tum.de/research/vslam/direct-shape|Project Page]]. |
| <html><center><iframe width="640" height="360" src="https://www.youtube.com/embed/QqP6zdx5OKw" frameborder="0" allowfullscreen></iframe></center></html> |
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| === Classic VO / SLAM === |
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* ** Stereo DSO ** This video shows some results of our paper "Stereo DSO: Large-Scale Direct Sparse Visual Odometry with Stereo Cameras" accepted by ICCV 2017. ([[https://vision.in.tum.de/research/vslam/stereo-dso|Project Page]]) | * ** Stereo DSO ** This video shows some results of our paper "Stereo DSO: Large-Scale Direct Sparse Visual Odometry with Stereo Cameras" accepted by ICCV 2017. ([[https://vision.in.tum.de/research/vslam/stereo-dso|Project Page]]) |
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=== Deep Learning Boosted VO / SLAM === | === VO / SLAM with Deep Learning === |
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* ** Deep Virtual Stereo Odometry (DVSO) ** In this project we design a novel deep network and train it in a semi-supervised way to predict depth map from single image, and integrate the depth map into DSO as virtual stereo measurement. Being a monocular VO approach, DVSO achieves comparable performance to the state-of-the-art stereo methods. ([[:research:vslam:dvso|Project Page]]) | * ** DVSO: Deep Virtual Stereo Odometry ** In this project we design a novel deep network and train it in a semi-supervised way to predict depth map from single image, and integrate the depth map into DSO as virtual stereo measurement. Being a monocular VO approach, DVSO achieves comparable performance to the state-of-the-art stereo methods. ([[https://vision.in.tum.de/research/vslam/dvso|Project Page]]) |
<html><center><iframe width="640" height="360" | <html><center><iframe width="640" height="360" |
src="https://www.youtube.com/embed/sLZOeC9z_tw" frameborder="0" allowfullscreen></iframe> | src="https://www.youtube.com/embed/sLZOeC9z_tw" frameborder="0" allowfullscreen></iframe> |
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==== Master Theses / IDP / Guided Research ==== | |
Please send me your transcripts and CV by email. | |
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==== Teaching ==== | ==== Teaching ==== |
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==== Service ==== | ==== Service ==== |
Reviewer: CVPR, ICCV, ICRA, IROS, RA-L | * Conference reviewer: CVPR, ICCV, ECCV, ICRA, IROS, AAAI |
| * Journal reviewer: RA-L, T-RO, AURO |
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==== Publications ==== | ==== Publications ==== |