Katharina Roth

(RPTU University Kaiserslautern-Landau)
hosted by Seminar Series on Scientific Computing

"Generative Visualization Techniques for Urban Planning"

Generative AI models have experienced a dramatic increase in interest over the past decade. The potential of these technologies has expanded across diverse domains, including urban planning, with model requirements typically varying based on specific application tasks. In the context of urban planning, architects are normally tasked with creating presentation drafts that visualize proposed buildings within their urban context. One potential way to develop a generative AI model for automatically generating architectural presentation images in urban scenes is outlined in this seminar. Here, the integration of specific style guidelines into the model’s training process through the loss function is targeted. Flow Matching was utilized as the base generative AI type. In this talk, an overview of different generative AI model types is given as well as groundings about the application field of urban planning. A basic introduction in flow matching and two prominent variants of it. Furthermore, the current status of the developed model, called Mask-based Weighted Flow Matching (MWFM), is presented. It advances Unconditional Flow Matching by introducing innovative techniques that enable precise feature focusing through application-specific contextual masks. The final part of the seminar deals with the evaluation of the developed models in relation to the application style guidelines.

Time:	Thursday, 29.01.2026, 10:15
Place:	Hybrid (Room 32-349 and via Zoom)
Video:	https://uni-kl-de.zoom-x.de/j/69269239534?pwd=Z9UOzMpkhMjrxVhll3d49sNHFe9Fd1.1

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