论文标题
与地理空间的关注接近/遥感接近/遥感
Revisiting Near/Remote Sensing with Geospatial Attention
论文作者
论文摘要
这项工作解决了可用的辅助地面图像时盖帽图像分割的任务。最近的工作表明，对这两种方式进行联合推断（通常称为近遥感）可以提高准确性。扩展了这一工作，我们介绍了地理空间注意的概念，这是一种几何学意识到的注意机制，该机制明确考虑了地面图像和地理位置中像素之间的地理空间关系。我们提出了一种计算地理空间注意力的方法，该方法结合了几何特征以及顶部和地面图像的外观。我们介绍了一种基于地理空间注意的近遥感的新型体系结构，并证明了其用于五个分割任务的使用。结果表明，我们的方法显着优于先前的最新方法。
This work addresses the task of overhead image segmentation when auxiliary ground-level images are available. Recent work has shown that performing joint inference over these two modalities, often called near/remote sensing, can yield significant accuracy improvements. Extending this line of work, we introduce the concept of geospatial attention, a geometry-aware attention mechanism that explicitly considers the geospatial relationship between the pixels in a ground-level image and a geographic location. We propose an approach for computing geospatial attention that incorporates geometric features and the appearance of the overhead and ground-level imagery. We introduce a novel architecture for near/remote sensing that is based on geospatial attention and demonstrate its use for five segmentation tasks. The results demonstrate that our method significantly outperforms the previous state-of-the-art methods.
