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TUM-FA\c{C}ADE: Reviewing and enriching point cloud benchmarks for fa\c{c}ade segmentation. (arXiv:2304.07140v1 [cs.CV])
cs.LG updates on arXiv.org arxiv.org
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 urban interpretation methods. Yet, few researchers
have addressed the use of point cloud benchmarks for fa\c{c}ade segmentation.
Robust fa\c{c}ade segmentation is becoming a key factor in various applications
ranging from simulating autonomous driving functions to preserving cultural
heritage. In this work, we present a method of enriching existing point cloud
datasets with …
applications arxiv autonomous autonomous driving benchmark benchmarks cloud dataset datasets driving heritage interpretation mapping researchers segmentation types work