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Change Detection Meets Visual Question Answering
Zhenghang Yuan, Lichao Mou, Zhitong Xiong +1
The Earth's surface is continually changing, and identifying changes plays an important role in urban planning and sustainability. Although change detection techniques have been su…
Large-scale Building Height Retrieval from Single SAR Imagery based on Bounding Box Regression Networks
Yao Sun, Lichao Mou, Yuanyuan Wang +2
Building height retrieval from synthetic aperture radar (SAR) imagery is of great importance for urban applications, yet highly challenging owing to the complexity of SAR data. Thi…
Segmentation of VHR EO Images using Unsupervised Learning
Sudipan Saha, Lichao Mou, Muhammad Shahzad +1
Semantic segmentation is a crucial step in many Earth observation tasks. Large quantity of pixel-level annotation is required to train deep networks for semantic segmentation. Eart…
SCIDA: Self-Correction Integrated Domain Adaptation from Single- to Multi-label Aerial Images
Tianze Yu, Jianzhe Lin, Lichao Mou +3
Most publicly available datasets for image classification are with single labels, while images are inherently multi-labeled in our daily life. Such an annotation gap makes many pre…
Bi-Temporal Semantic Reasoning for the Semantic Change Detection in HR Remote Sensing Images
Lei Ding, Haitao Guo, Sicong Liu +3
Semantic change detection (SCD) extends the multi-class change detection (MCD) task to provide not only the change locations but also the detailed land-cover/land-use (LCLU) catego…
Self-supervised Audiovisual Representation Learning for Remote Sensing Data
Konrad Heidler, Lichao Mou, Di Hu +5
Many current deep learning approaches make extensive use of backbone networks pre-trained on large datasets like ImageNet, which are then fine-tuned to perform a certain task. In r…