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ZAHA

ZAHA is currently the largest benchmark dataset for point‑cloud façade semantic segmentation, containing 601 million labeled points, introducing the Facade Generalisation Level (LoFG) to support hierarchical understanding of building façades, covering diverse architectural styles, and providing both local and global (UTM) coordinate reference systems.

Updated 11/7/2024
github

Description

ZAHA Dataset Overview

Dataset Introduction

ZAHA is presently the largest benchmark for point‑cloud façade semantic segmentation.

Highlights

  • 601 million labeled points
  • Introduces LoFG (Facade Generalisation Level) for hierarchical façade understanding
  • Covers multiple architectural styles
  • Provides local and global (UTM) coordinate reference systems
  • Filenames reference official Bavarian CityGML LoD2 building models
  • Includes configuration files for adding custom data

Segmentation Results

LoFG2 Results

ModelOAPRF1IoU
PointNet71.969.668.168.155.8
PointNet++75.573.073.072.659.8
Point Transformer78.275.876.676.163.9
DGCNN82.680.081.880.468.5

LoFG3 Results

ModelOAPRF1IoU
PointNet59.946.142.238.726.4
PointNet++66.437.835.934.825.6
Point Transformer75.052.754.752.141.6
DGCNN71.153.645.844.533.4

Download

Citation

@article{wysockietalZAHA,
  author = {Wysocki, O. and Tan, Y. and Froech, T. and Xia, Y. and Wysocki, M. and Hoegner, L. and Cremers, D. and Holst, C.},
  title = {ZAHA: Introducing the Level of Facade Generalization and the Large‑Scale Point Cloud Facade Semantic Segmentation Benchmark Dataset},
  booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
  year = {2025},
}

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Topics

Point Cloud Data
Facade Analysis

Source

Organization: github

Created: 11/6/2024

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