I received my M.Sc. in Information Technology from the University of Stuttgart and then worked for 4 years as a Computer Vision & Artificial Intelligence engineer in Artisense co-founded by Prof. Dr. Daniel Cremers. Currently, I'm a Ph.D. student in the Computer Vision Group, headed by Prof. Dr. Daniel Cremers at TUM.

My research interests lie in visual-based 3D reconstruction, 2D/3D scene understanding, and 3D asset/scene generation.

I am looking for collaborators and motivated students for research projects. Feel free to get in touch with me via email.

Currently, research works like LERF, OpenNERF have successfully embedded semantic features from foundation vision models (CLIP, DINOv2) into the volumetric neural representations. However, applying these techniques to dynamic scenes remains an open research challenge. In this master’s thesis, you will work on reconstructing dynamic scenes using neural radiance fields from temporal image sequences or videos. The goal is to enhance these reconstructions with the ability to comprehend open vocabulary semantics.

Preferred Requirements:

• Strong motivation in research with a focus on achieving publication.
• Strong background in 3D computer vision and neural radiance field rendering (e.g., NeRF, 3DGS).
• Proficiency in Python and C++ (For CUDA), and PyTorch.
• The project lasts 6 months or so and is suitable for a master thesis.

If you are interested, please contact me via email with your CV/transcript/motivation attached.

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Journal Articles
2024
[]		HI-SLAM: Monocular Real-Time Dense Mapping With Hybrid Implicit Fields (W Zhang, T Sun, S Wang, Q Cheng and N Haala), In IEEE Robotics and Automation Letters (RAL) & Int. Conference on Intelligent Robots and Systems (IROS), volume 9, 2024.  [bibtex] [arXiv:2310.04787]Oral Presentation
Preprints
2024
[]		HI-SLAM2: Geometry-Aware Gaussian SLAM for Fast Monocular Scene Reconstruction (W Zhang, Q Cheng, D Skuddis, N Zeller, D Cremers and N Haala), In arXiv preprint arXiv:2411.17982, 2024.  [bibtex] [pdf]
Conference and Workshop Papers
2022
[]		Vision-Based Large-scale 3D Semantic Mapping for Autonomous Driving Applications (Q Cheng, N Zeller and D Cremers), In International Conference on Robotics and Automation (ICRA), 2022.  [bibtex] [arXiv:2203.01087]
2020
[]		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. ([project page][arXiv][video]) [bibtex] [pdf]