Recently, the optimization of existing buildings, especially in Germany (up to 80 % of all projects), has increased sharply, with the focus on the energy-efficent refurbishment of post-war residential buildings. In the coming years, residential buildings built up to 1918 (15 %) and from 1920 to 1940 (13 %) offer great potential for saving energy.

Challenges arise due to unavailable or outdated plans and data; therefore complex building surveys are needed. Unlike new buildings, existing ones evolve throughout their life cycle, making investigation a "reverse design and planning process." This involves measuring "visible" surfaces/points and using additional documentations and partial finds, and crucial domain knowledge is forgotten today.

Replicating existing buildings precisely is impossible, resulting in imperfect models. NERF2BIM addresses these challenges by leveraging AI advancements to introduce a detailing-on-demand strategy, enhancing the existing BIM methodology with variable information integration, as follows:
I. Enhance point cloud-based surveys by addressing acquisition, georeferencing, and uncertainty quantification, focusing on sustainable solutions. Improve scanning performance and reliability through strategies for evaluating and documenting uncertainty.
II. Develop Semantic 3D Understanding for automatic labelling of indoor and outdoor acquisitions, building on the NeRF model to integrate 2D and 3D data. This enables accurate 3D-consistent semantic understanding of BIM parts in raw 3D scans, alongside simple BIM Component Reconstruction using geometric representations.
III. Apply Component Detailing to "simple" BIM Components, leveraging a knowledge base with architectural insights. Employ novel AI methods to introduce a user feedback system, refining the system continuously.

Principal Investigators 

Prof. Dr.-Ing. Frank Petzold
Chair of Architectural Informatics, TUM School of Engineering and Design

Prof. Dr.-Ing. Matthias Niessner
Chair of Visual Computing and Artificial Intelligence, TUM School of Computation, Information and Technology 

Prof. Dr.-Ing. Christoph Holst
Chair of Engineering Geodesy, TUM School of Engineering and Design

The duration is from November 2024 until September 2028.

The Research Unit is funded by TUM Georg Nemetschek Institute Artificial Intelligence for the Built World