Direkt zum Inhalt springen
Computer Vision Group
TUM Department of Informatics
Technical University of Munich

Technical University of Munich

Menu
Home Members Rui Wang

Differences

This shows you the differences between two versions of the page.

Link to this comparison view

Both sides previous revision Previous revision
Next revision
Previous revision
members:wangr [2019/07/10 16:10]
Rui Wang
members:wangr [2019/10/09 13:54] (current)
Rui Wang
Line 6: Line 6:
   * [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 recently founded 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. 
  
  
 ==== 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. 
  
 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]],
Line 20: Line 19:
 === Semantic VO / SLAM === === Semantic VO / SLAM ===
  
-  * ** Direct Shape ** 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 paper [[https://​arxiv.org/​abs/​1904.10097|arXiv]]. ​(The project page is under construction.) ​+  * ** Direct Shape ** 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 paper [[https://​arxiv.org/​abs/​1904.10097|arXiv]] ​and 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>​ <​html><​center><​iframe width="​640"​ height="​360"​ src="​https://​www.youtube.com/​embed/​QqP6zdx5OKw"​ frameborder="​0"​ allowfullscreen></​iframe></​center></​html>​
 <​html><​br /></​html>​ <​html><​br /></​html>​
Line 42: Line 41:
 === Deep Learning Boosted VO / SLAM === === Deep Learning Boosted VO / SLAM ===
  
-  * ** 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]])+  * ** 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. ([[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>​
Line 64: Line 63:
  
 ==== Service ==== ==== Service ====
-Reviewer: CVPR, ICCV, ICRA, IROS, RA-L+  * Conference reviewer: CVPR, ICCV, ICRA, IROS, AAAI¬†
 +  * Journal reviewer: ​RA-L, T-RO
  
 ==== Publications ==== ==== Publications ====

Rechte Seite

Informatik IX
Chair of Computer Vision & Artificial Intelligence

Boltzmannstrasse 3
85748 Garching

info@vision.in.tum.de