WUP-CD: TOWARDS 2.5D DATA FOR DEEP LEARNING BUILDING CHANGE DETECTION

被引：0

作者：

Bauer, Adrian ^{[1
]}

Oberbossel, Jens ^{[2
]}

Sander, Stefan ^{[2
]}

Kummert, Anton ^{[1
]}

机构：

[1] Univ Wuppertal, Sch Elect Informat & Media Engn, D-42119 Wuppertal, Germany

[2] City Adm Wuppertal, D-42275 Wuppertal, Germany

来源：

2022 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2022) | 2022年

关键词：

Change Detection (CD); Remote Sensing Dataset; Deep Learning; Digital Surface Model; 2.5D Data;

D O I：

10.1109/IGARSS46834.2022.9883863

中图分类号：

P [天文学、地球科学];

学科分类号：

07 ;

摘要：

We present WUP-CD, a high-resolution aerial dataset for building change detection consisting of both orthorectified aerial imagery and corresponding elevation information acquired at two points in time. Detailed analysis of the dataset using several state-of-the-art deep learning methods allows us to show that the best results are obtained using elevation data only, highlighting its importance for future data acquisition and model development. The dataset is available for download (1).

引用

页码：219 / 222

页数：4

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