most citedCombining visibility analysis and deep learning for refinement of semantic 3D building models by conflict classification

19 citations · 35 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2024

Transferring facade labels between point clouds with semantic octrees while considering change detection

Sophia Schwarz, Tanja Pilz, Olaf Wysocki +2

Point clouds and high-resolution 3D data have become increasingly important in various fields, including surveying, construction, and virtual reality. However, simply having this d…

cs.CV2024

Reconstructing facade details using MLS point clouds and Bag-of-Words approach

Thomas Froech, Olaf Wysocki, Ludwig Hoegner +1

In the reconstruction of façade elements, the identification of specific object types remains challenging and is often circumvented by rectangularity assumptions or the use of boun…

cs.CV2024

Classifying point clouds at the facade-level using geometric features and deep learning networks

Yue Tan, Olaf Wysocki, Ludwig Hoegner +1

3D building models with facade details are playing an important role in many applications now. Classifying point clouds at facade-level is key to create such digital replicas of th…

cs.CV2024

MLS2LoD3: Refining low LoDs building models with MLS point clouds to reconstruct semantic LoD3 building models

Olaf Wysocki, Ludwig Hoegner, Uwe Stilla

Although highly-detailed LoD3 building models reveal great potential in various applications, they have yet to be available. The primary challenges in creating such models concern…

cs.CV20232 cited

Scan2LoD3: Reconstructing semantic 3D building models at LoD3 using ray casting and Bayesian networks

Olaf Wysocki, Yan Xia, Magdalena Wysocki +4

Reconstructing semantic 3D building models at the level of detail (LoD) 3 is a long-standing challenge. Unlike mesh-based models, they require watertight geometry and object-wise s…

cs.CV202314 cited

TUM-FAÇADE: Reviewing and enriching point cloud benchmarks for façade segmentation

Olaf Wysocki, Ludwig Hoegner, Uwe Stilla

Point clouds are widely regarded as one of the best dataset types for urban mapping purposes. Hence, point cloud datasets are commonly investigated as benchmark types for various u…