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Nan Yang

PhD student

Technische Universität München

Department of Computer Science
Informatik 9
Boltzmannstrasse 3
85748 Garching
Germany

Tel: +49-89-289-17792
Fax: +49-89-289-17757
Office: 02.09.059
Mail: yangn@in.tum.de

News

  • [07.2018] One paper accepted for ECCV 2018 (oral), Munich.
  • [06.2018] One paper accepted for IROS 2018, Madrid.
  • [05.2018] One paper accepted for publication in RA-L.

Research Interests

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

Deep Virtual Stereo Odometry (DVSO) – Project Page


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 PhD student and senior computer vision & AI researcher in Artisense, a startup co-founded by Prof. Daniel Cremers.

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 IEEE Robotics and Automation Letters (RA-L), volume 3, 2018. (This paper was also selected by IROS'18 for presentation at the conference.[arxiv]) [bibtex] [doi] [pdf]
Preprints
2019
[]DirectShape: Photometric Alignment of Shape Priors for Visual Vehicle Pose and Shape Estimation (R. Wang, N. Yang, J. Stueckler and D. Cremers), In preprint, 2019. ([arxiv][video] [project page]) [bibtex]
Conference and Workshop Papers
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.  [bibtex]
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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Rechte Seite

Informatik IX
Chair of Computer Vision & Artificial Intelligence

Boltzmannstrasse 3
85748 Garching

info@vision.in.tum.de