| Name: | Jan Frederick Eick, M.Sc. |
| Room: | Bauhausstraße 11, room 006 |
| Phone: | +49 (0) 36 43/58 37 23 |
| E-Mail: | jan-frederick.eick[at]uni-weimar.de |
| Office Hours: | On request |
| Teaching: | Applied Deep Learning for Computer Shape of you: 3D Semantic Segmentation of Point Cloud Data Generating 3D Interior Design for Point Cloud Scene Understanding and Room Layout Analysis Neural Radiance Fields (NeRF) for 3reCapSL Capturing Device |
| Research: | 3D Semantic Segmentation of Point Clouds, Stereo Matching, Photogrammetry |
Jan Frederick Eick is a research assistant at the Computer Science department at Bauhaus University Weimar since July 2020.
Before that, he completed his studies in the Computer Science department as a MSc with his master's thesis "Deep Learning based Stereo Matching for High-Resolution Images".
His research interests include various disciplines of computer vision, in particular automatic semantic segmentation of point clouds using machine learning methods.
Ongoing Research
- MetaReal - Immersive communication, collaboration and intelligent services in a digital world copy
Publications
- Morgenthal, G., Eick, J. F., Rau, S., & Taraben, J. (2019). Wireless Sensor Networks Composed of Standard Microcomputers and Smartphones for Applications in Structural Health Monitoring. Sensors, 19(9), 2070. https://doi.org/10.3390/s19092070
Betreute Abschlussarbeiten
Master's theses:
El Mehdi Essadki: A Framework for Guided 3D Point Cloud Annotation, WiSe 2021/22
Huy Khanh Ha: Real-time multi-view marker-less motion capture of multiple humans, SoSe 2021
Bachelor's theses:
Martin Tippmann: Retrieval of 3D Point Cloud Submaps from 2D Query Images, WiSe 2022/23
Philipp Tornow: Unsupervised object extraction for semantic segmentation of bridge scenes, SoSe 2021