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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

  • [11.2020] MonoRec accepted at CVPR 2021.
  • [12.2020] Finished the internship at Facebook Reality Labs where I worked on efficient 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, arXiv preprint 2020.


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

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

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]
Preprints
2020
[]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 arXiv preprint, 2020. ([project page]) [bibtex] [arXiv:2011.11814]
Conference and Workshop Papers
2020
[]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]
[]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. ([arXiv][video]) [bibtex] [pdf]
[]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],[video],[talk],[project]) [bibtex]Oral Presentation
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News

25.01.2021

Rick Szeliski (University of Washington) will give a talk in the TUM AI lecture series on Jan 28th, 5pm! Livestream

10.12.2020

Frank Dellaert (Georgia Tech) will give a talk in the TUM AI lecture series on Dec 17th, 4pm! Livestream

15.10.2020

Jon Barron (Google) will give a talk in the TUM AI lecture series on Oct 22nd, 9pm! Livestream

02.10.2020

We have five papers accepted to 3DV 2020!

30.09.2020

Our effcient deep network architectures form the AI engine of the project Slow Down COVID-19 at Harvard.

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