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Computer Vision Group
TUM Department of Informatics
Technical University of Munich

Technical University of Munich

Home Members Nan Yang

Nan Yang

PhD student

Technische Universität München

Department of Computer Science
Informatik 9
Boltzmannstrasse 3
85748 Garching

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

Find me on Google Scholar, Linkedin.


  • [05.2020] We are organizing a workshop together with a challenge on Map-based Localization for Autonomous Driving at ECCV 2020 (page).
  • [02.2020] D3VO accepted at CVPR 2020, Seattle (arxiv).
  • [01.2020] DirectShape accepted at ICRA 2020, Paris (project page).
  • [09.2019] MF-GAN accepted at CoRL 2019, Osaka (arxiv,video).
  • [07.2018] DVSO accepted at ECCV 2018, Munich (project page).
  • [06.2018] Challenges in MonoVO accepted at RA-L and IROS 2018, Madrid (arxiv).

Research Interests

My research interests lie in incorporating deep learning into classical visual odometry and SLAM.

Brief Bio

Nan Yang received his Bachelor's degree in Computer Science from Beijing University of Posts and Telecommunications and his Master's degree in Informatics from the Technical University of Munich. Since May 2018, he is a Ph.D. student and senior computer vision researcher in Artisense, a startup co-founded by Prof. Daniel Cremers.

Professional Services

  • Journal reviewer: RA-L
  • Conference reviewer: CVPR, ECCV, ICCV, AAAI, ICRA, IROS


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Journal Articles
[]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
[]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]
[]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
[]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],[video],[talk],[project]) [bibtex]Oral Presentation
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Rechte Seite

Informatik IX
Chair of Computer Vision & Artificial Intelligence

Boltzmannstrasse 3
85748 Garching