Nan Yang / 杨楠


I'm a senior research scientist at Reality Labs Research, Meta. I pursued my PhD at Technical University of Munich (TUM), supervised by Prof. Daniel Cremers. During my PhD, I was also a senior computer vision engineer at Artisense, a startup co-founded by Prof. Cremers. Prior to my PhD, I obtained my Master’s degree at TUM and my Bachelor’s degree at Beijing University of Posts and Telecommunications.

My research interest is to leverage the power of Deep Neural Networks to overcome the limitations in traditional 3D computer vision and visual SLAM, such as visual odometry, relocalization, and dense mapping.

News

Publications

F. Wimbauer, N. Yang, C. Rupprecht, and D. Cremers
Behind the Scenes: Density Fields for Single View Reconstruction
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023
X. Zuo, N. Yang, N. Merrill, , B. Xu, and S. Leutenegger
Incremental Dense Reconstruction from Monocular Video with Guided Sparse Feature Volume Fusion
IEEE Robotics and Automation Letters (RA-L), 2023
L. Köstler*, N. Yang*, N. Zeller, and D. Cremers (*equal contribution)
TANDEM: Tracking and Dense Mapping in Real-time using Deep Multi-view Stereo
Conference on Robot Learning (CoRL), 2021
Best Demo Award at 3DV 2021
F. Wimbauer*, N. Yang*, N. Zeller, and D. Cremers (*equal contribution)
MonoRec: Semi-Supervised Dense Reconstruction in Dynamic Environments from a Single Moving Camera
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021
L. von Stumberg, P. Wenzel, N. Yang, and D. Cremers
LM-Reloc: Levenberg-Marquardt Based Direct Visual Relocalization
International Conference on 3D Vision (3DV), 2020
P. Wenzel, R. Wang, N. Yang, Q. Khan, Q. Cheng, L. von Stumberg, N. Zeller, and D. Cremers
4Seasons: A Cross-Season Dataset for Multi-Weather SLAM in Autonomous Driving
German Conference on Pattern Recognition (GCPR), 2020
L. Köstler, N. Yang, R. Wang, and D. Cremers
Learning Monocular 3D Vehicle Detection without 3D Bounding Box Labels
German Conference on Pattern Recognition (GCPR), 2020
N. Yang, L. von Stumberg, R. Wang, and D. Cremers
D3VO: Deep Depth, Deep Pose and Deep Uncertainty for Monocular Visual Odometry
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020
Oral Presentation
R. Wang, N. Yang, J. Stückler, and D. Cremers
DirectShape: Photometric Alignment of Shape Priors for Visual Vehicle Pose and Shape Estimation
IEEE International Conference on Robotics and Automation (ICRA), 2020
E. Jung*, N. Yang*, and D. Cremers (*equal contribution)
Multi-Frame GAN: Image Enhancement for Stereo Visual Odometry in Low Light
Conference on Robot Learning (CoRL), 2019
Full Oral Presentation
N. Yang, R. Wang, J. Stückler, and D. Cremers
Deep Virtual Stereo Odometry: Leveraging Deep Depth Prediction for Monocular Direct Sparse Odometry
European Conference on Computer Vision (ECCV), 2018
Oral Presentation
N. Yang*, R. Wang*, X. Gao, and D. Cremers (*equal contribution)
Challenges in Monocular Visual Odometry: Photometric Calibration, Motion Bias and Rolling Shutter Effect
IEEE Robotics and Automation Letters (RA-L) & Int. Conference on Intelligent Robots and Systems (IROS), 2018

Reviewer

Workshop Organizer