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Technical University of Munich

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Nan Yang

PhD student

Technical University of Munich

Department of Informatics
Informatics 9
Boltzmannstrasse 3
85748 Garching
Germany

Fax: +49-89-289-17757
Office: 
Mail: yangn@in.tum.de

  • [04.2021] 4Seasons dataset is now public.
  • [03.2021] MonoRec accepted at CVPR 2021. Code will be released soon.
  • [12.2020] Finished the internship at Facebook Reality Labs where I worked on collaborative mapping.
  • [10.2020] LM-Reloc accepted at 3DV 2020.
  • [09.2020] Started the internship at Facebook Reality Labs.
  • [08.2020] Two papers accepted at GCPR 2020.
  • [05.2020] Co-organized Map-based Localization for Autonomous Driving Workshop, ECCV 2020.
  • [02.2020] D3VO accepted as an oral presentation at CVPR 2020.

Brief Bio

Find me on Google Scholar, Linkedin, Twitter.

I received my Bachelor's degree in Computer Science from Beijing University of Posts and Telecommunications and my Master's degree in Informatics from the Technical University of Munich. Since May 2018, I am a Ph.D. student and senior computer vision researcher in Artisense, a startup co-founded by Prof. Daniel Cremers. From September 2020 until December 2020, I was an intern in Facebook Reality Labs working on collaborative mapping.

Research

My research interest lies in enhancing classical 3D vision, e.g., visual odometry / simultaneously localization and mapping (SLAM), re-localization, and dense reconstruction, with the aid of deep neural networks. Here are some selected projects:

Visual Odometry

  • Deep Virtual Stereo Odometry: Leveraging Deep Depth Prediction for Monocular Direct Sparse Odometry, ECCV 2018.


  • D3VO: Deep Depth, Deep Pose and Deep Uncertainty for Monocular Visual Odometry, CVPR 2020.


  • Multi-Frame GAN: Image Enhancement for Stereo Visual Odometry in Low Light , CoRL 2019.


Dense Reconstruction

  • MonoRec: Semi-Supervised Dense Reconstruction in Dynamic Environments from a Single Moving Camera, CVPR 2021.


Re-localization

  • LM-Reloc: Levenberg-Marquardt Based Direct Visual Relocalization, 3DV 2020.


Object-level Perceptions

  • DirectShape: Photometric Alignment of Shape Priors for Visual Vehicle Pose and Shape Estimation, ICRA 2020.


  • Learning Monocular 3D Vehicle Detection without 3D Bounding Box Labels, GCPR 2020.


Professional Services

Publications


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Journal Articles
2018
[]Challenges in Monocular Visual Odometry: Photometric Calibration, Motion Bias and Rolling Shutter Effect (N. Yang, R. Wang, X. Gao and D. Cremers), In In IEEE Robotics and Automation Letters (RA-L) & Int. Conference on Intelligent Robots and Systems (IROS), volume 3, 2018. ([arxiv]) [bibtex] [doi] [pdf]
Conference and Workshop Papers
2021
[]MonoRec: Semi-Supervised Dense Reconstruction in Dynamic Environments from a Single Moving Camera (F. Wimbauer, N. Yang, L. von Stumberg, N. Zeller and D Cremers), In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021. ([project page]) [bibtex] [arXiv:2011.11814]
2020
[]4Seasons: A Cross-Season Dataset for Multi-Weather SLAM in Autonomous Driving (P. Wenzel, R. Wang, N. Yang, Q. Cheng, Q. Khan, L. von Stumberg, N. Zeller and D. Cremers), In Proceedings of the German Conference on Pattern Recognition (GCPR), 2020. ([project page][arXiv][video]) [bibtex] [pdf]
[]LM-Reloc: Levenberg-Marquardt Based Direct Visual Relocalization (L. von Stumberg, P. Wenzel, N. Yang and D. Cremers), In International Conference on 3D Vision (3DV), 2020. ([arXiv][project page][video][supplementary][poster]) [bibtex]
[]Learning Monocular 3D Vehicle Detection without 3D Bounding Box Labels (L. Koestler, N. Yang, R. Wang and D. Cremers), In Proceedings of the German Conference on Pattern Recognition (GCPR), 2020. ([project page][video]) [bibtex] [pdf]
[]D3VO: Deep Depth, Deep Pose and Deep Uncertainty for Monocular Visual Odometry (N. Yang, L. von Stumberg, R. Wang and D. Cremers), In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020.  [bibtex] [arXiv:2003.01060] [pdf]Oral Presentation
[]DirectShape: Photometric Alignment of Shape Priors for Visual Vehicle Pose and Shape Estimation (R. Wang, N. Yang, J. Stueckler and D. Cremers), In Proc. of the IEEE International Conference on Robotics and Automation (ICRA), 2020. ([video][presentation][project page][supplementary][arxiv]) [bibtex] [pdf]
2019
[]Multi-Frame GAN: Image Enhancement for Stereo Visual Odometry in Low Light (E. Jung, N. Yang and D. Cremers), In Conference on Robot Learning (CoRL), 2019. ([arxiv],[supplementary],[video]) [bibtex]Full Oral Presentation
2018
[]Deep Virtual Stereo Odometry: Leveraging Deep Depth Prediction for Monocular Direct Sparse Odometry (N. Yang, R. Wang, J. Stueckler and D. Cremers), In European Conference on Computer Vision (ECCV), 2018. ([arxiv],[supplementary],[project]) [bibtex]Oral Presentation
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News

05.05.2021
French-German Machine Learning Symposium

French-German Machine Learning Symposium

The French-German Machine Learning Symposium aims to strengthen interactions and inspire collaborations between both countries. We invited some of the leading ML researchers from France and Germany to this two-day symposium to give a glimpse into their research, and engage in discussions on the future of machine learning and how to strengthen research collaborations in ML between France and Germany.

The list of speakers includes Yann LeCun, Cordelia Schmid, Jean-Bernard Lasserre, Bernhard Schölkopf, and many more! For the full program please visit the webpage.

03.05.2021

Ron Kimmel (Technion - Israel Institute of Technology) will give a talk in the TUM AI lecture series on May 6th, 3pm! Livestream

23.04.2021

4Seasons Dataset: We have released a novel dataset for benchmarking multi-weather SLAM in autonomous driving.

19.04.2021

Hao Li (Pinscreen) will give a talk in the TUM AI lecture series on April 22nd, 8pm! Livestream

07.04.2021

Thomas Pock (TU Graz) will give a talk in the TUM AI lecture series on April 15th, 3pm! Livestream

More