MapAI: Precision in Building Segmentation
Fuente:
arXiv
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| Autori principali: | , , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| Soggetti: | |
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| _version_ | 1866916085477933056 |
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| author | Jyhne, Sander Riisøen Goodwin, Morten Andersen, Per Arne Oveland, Ivar Nossum, Alexander Salveson Ormseth, Karianne Ørstavik, Mathilde Flatman, Andrew C. |
| author_facet | Jyhne, Sander Riisøen Goodwin, Morten Andersen, Per Arne Oveland, Ivar Nossum, Alexander Salveson Ormseth, Karianne Ørstavik, Mathilde Flatman, Andrew C. |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_04406 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | MapAI: Precision in Building Segmentation Jyhne, Sander Riisøen Goodwin, Morten Andersen, Per Arne Oveland, Ivar Nossum, Alexander Salveson Ormseth, Karianne Ørstavik, Mathilde Flatman, Andrew C. Computer Vision and Pattern Recognition 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. |
| title | MapAI: Precision in Building Segmentation |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2401.04406 |