Hannah Schieber, PhD Student

Bio

I am a PhD student under the supervision of Prof Daniel Roth at the Technical University Munich (TUM). My research focuses on radiance field, digital replicas, 6D pose estimation, and guidance in 3D using extended reality (XR), with an emphasis on novel view synthesis and the enhancement of classic 3D reconstruction through computer vision. Specifically, I investigate how editable 3D Gaussian Splatting can serve as a flexible and efficient scene representation. This includes enabling interactive editing of reconstructed environments, integrating semantic information, and supporting novel-view synthesis directly within XR systems. By enhancing classic 3D reconstruction pipelines with modern vision techniques, my research aims to create more immersive, accurate, and adaptable digital replicas for XR.
Moreover, I guide as a tutor several courses like: Advanced Topics in 3D Computer Vision or Modern Computer Vision Methods
In winter term 2024/2025, I hold the seminar Computer Vision in the Operating Room @ TUM.

Visiting Research

In the first half of 2024, I was a visiting PhD student at the University of Otago, New Zealand. There I researched the creation of outdoor 3D scenes for Virtual Reality using Neural Rendering in the Visual Computing Group under the supervision of Prof. Stefanie Zollmann. The results from this research visit can be found here: Project Page

Education

Prior my PhD position, I received my bachelor’s degree from HS Aalen, and my master’s degree from TH Ingolstadt, both in computer science. I did my master's degree in the AUDI DUAL master program. During my bachelor studies, I gained experience in the industry at MAPAL Dr. Kress KG, c-Com GmbH and Carl Zeiss AG.

I am interested in computer vision, extended reality and in general in many things in life. Besides being passionate about my PhD studies I like to go cycling and bouldering.

Interested in a research coperation? Feel free to contact me any time via e-mail:

Contact:
hannah dot schieber @ tum dot de  /  Google Scholar  /  bsky.social /  Twitter  /  Github

Awards

Drawings