MapAI: Precision in Building Segmentation is a competition arranged with the Norwegian Artificial Intelligence Research Consortium (NORA) in collaboration with Centre for Artificial Intelligence Research at the University of Agder (CAIR), the Norwegian Mapping Authority, AI:Hub, Norkart, and the Danish Agency for Data Supply and Infrastructure. The competition will be held in the fall of 2022. It will be concluded at the Northern Lights Deep Learning conference focusing on the segmentation of buildings using aerial images and laser data. We propose two different tasks to segment buildings, where the first task can only utilize aerial images, while the second must use laser data (LiDAR) with or without aerial images. Furthermore, we use IoU and Boundary IoU to properly evaluate the precision of the models, with the latter being an IoU measure that evaluates the results' boundaries. We provide the participants with a training dataset and keep a test dataset for evaluation.

翻译：MapAI：建筑分割的精准度是一项由挪威人工智能研究联盟（NORA）与阿格德尔大学人工智能研究中心（CAIR）、挪威测绘局、AI:Hub、Norkart以及丹麦数据供应与基础设施局合作举办的竞赛。该竞赛将于2022年秋季举行，并在北极光深度学习会议上总结成果，聚焦于利用航拍图像和激光数据对建筑进行分割。我们提出了两个不同的建筑分割任务：第一个任务仅能使用航拍图像，而第二个任务必须使用激光数据（LiDAR），可选是否结合航拍图像。此外，我们采用IoU和边界IoU来恰当评估模型的精准度，其中后者是一种评估结果边界的IoU度量。我们向参赛者提供训练数据集，并保留测试数据集用于评估。