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Nan Yang
PhD student
Technical University of MunichSchool of Computation, Information and Technology
Informatics 9
Boltzmannstrasse 3
85748 Garching
Germany
Fax: +49-89-289-17757
Office:
Mail: yangn@in.tum.de
Find me on Google Scholar, Linkedin.
News
- [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).
- [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
I received my 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, I am a Ph.D. student and senior computer vision researcher in Artisense, a startup co-founded by Prof. Daniel Cremers. Starting in September 2020, I do an internship in Facebook Reality Labs working on efficient collaborative on-device mapping. I'm open to work opportunities starting in 2021.
Professional Services
- Journal reviewer: RA-L
- 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 , In In IEEE Robotics and Automation Letters (RA-L) & Int. Conference on Intelligent Robots and Systems (IROS), volume 3, 2018. ([arxiv])
Preprints
2022
[] 4Seasons: Benchmarking Visual SLAM and Long-Term Localization for Autonomous Driving in Challenging Conditions , In arXiv preprint arXiv:2301.01147, 2022.
Conference and Workshop Papers
2024
[] FIRe: Fast Inverse Rendering Using Directional and Signed Distance Functions , In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2024. ([Project page],[ArXiv])
2023
[] Behind the Scenes: Density Fields for Single View Reconstruction , In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023. ([project page])
2021
[] TANDEM: Tracking and Dense Mapping in Real-time using Deep Multi-view Stereo , In Conference on Robot Learning (CoRL), 2021. ([GitHub][video][project page])
3DV'21 Best Demo Award [] MonoRec: Semi-Supervised Dense Reconstruction in Dynamic Environments from a Single Moving Camera , In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021. ([project page])
2020
[] LM-Reloc: Levenberg-Marquardt Based Direct Visual Relocalization , In International Conference on 3D Vision (3DV), 2020. ([arXiv][project page][video][supplementary][poster])
[] 4Seasons: A Cross-Season Dataset for Multi-Weather SLAM in Autonomous Driving , In Proceedings of the German Conference on Pattern Recognition (GCPR), 2020. ([project page][arXiv][video])
[] Learning Monocular 3D Vehicle Detection without 3D Bounding Box Labels , In Proceedings of the German Conference on Pattern Recognition (GCPR), 2020. ([project page][video])
[] D3VO: Deep Depth, Deep Pose and Deep Uncertainty for Monocular Visual Odometry , In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020.
Oral Presentation [] DirectShape: Photometric Alignment of Shape Priors for Visual Vehicle Pose and Shape Estimation , In Proc. of the IEEE International Conference on Robotics and Automation (ICRA), 2020. ([video][presentation][project page][supplementary][arxiv])
2019
[] Multi-Frame GAN: Image Enhancement for Stereo Visual Odometry in Low Light , In Conference on Robot Learning (CoRL), 2019. ([arxiv],[supplementary],[video])
Full Oral Presentation
2018
[] Deep Virtual Stereo Odometry: Leveraging Deep Depth Prediction for Monocular Direct Sparse Odometry , In European Conference on Computer Vision (ECCV), 2018. ([arxiv],[supplementary],[project])
Oral Presentation