UnderOneFacade: Worldwide Facade Semantic Segmentation Benchmark Dataset

• URL: http://arxiv.org/abs/2607.02018v1
• Date: Thu, 02 Jul 2026 10:50:01 GMT
• Title: UnderOneFacade: Worldwide Facade Semantic Segmentation Benchmark Dataset
• Abstract summary: We introduce UnderOneFacade, the largest cross-country and cross-continent 3D facade benchmark to date.<n>We show that current methods struggle to recognize fine-grained architectural elements and degrade significantly across geographic domains.<n>UnderOneFacade establishes a rigorous benchmark for developing robust and transferable 3D segmentation models.
• Score: 19.044731989703468
• License: http://creativecommons.org/licenses/by-sa/4.0/
• Abstract: Globally consistent semantic digital twins require centimeter-accurate and geographically transferable 3D facade segmentation. However, progress in facade parsing is limited by the lack of large-scale, standardized benchmarks for evaluating cross-domain generalization. Existing datasets are geographically narrow, semantically inconsistent, or insufficiently precise. We introduce UnderOneFacade, the largest cross-country and cross-continent 3D facade benchmark to date, comprising centimeter-accurate point clouds with hierarchical, harmonized, and architecturally grounded semantic labels totaling 2.7 billion annotated points. Through a systematic evaluation of representative point-, graph- and transformer-based architectures, we show that current methods struggle to recognize fine-grained architectural elements and degrade significantly across geographic domains, with the best models achieving only up to 33 IoU on the fine-grained LoFG3 benchmark. By combining geometric precision with standardized semantics at unprecedented scale, UnderOneFacade establishes a rigorous benchmark for developing robust and transferable 3D segmentation models. The dataset, evaluation scripts, and pretrained models will be released upon publication.

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