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

Mar 2023: Behind the Scenes accepted at CVPR 2023.
Mar 2022: I've joined Reality Labs Research as a Research Scientist.
Dec 2021: TANDEM accepted at CoRL 2021 and won the Best Demo Award at 3DV 2021!
May 2021: Received Outstading Reviewer for CVPR 2021.
May 2018: Started PhD at CVAI of TUM supervised by Prof. Daniel Cremers.
Mar 2018: Joined Artisense as a senior computer vision & AI engineer.

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 Project / Paper / Code / Video
	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 Paper / Video
	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* Project / Paper / Code / Video
	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 Project / Paper / Code / Video
	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 Project / Paper
	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 Project / Paper
	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 Project / Paper
	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 Project / Paper
	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 Project / Paper
	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 Paper / Video
	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 Project / Paper
	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 Project / Paper

Reviewer

Computer Vision: CVPR, ECCV, ICCV, T-PAMI
Machine Learning: ICLR, AAAI, NeurIPS, PR
Robotics: ICRA, IROS, RA-L, AURO, ISPRS, T-RO
Computer Graphics: SIGGRAPH

Workshop Organizer

Map-based Localization for Autonomous Driving Workshop, ICCV 2021
Map-based Localization for Autonomous Driving Workshop, ECCV 2020