Precisely identifying pavement cracks from charge-coupled devices (CCDs) captured high-
resolution images faces many challenges. Even though convolutional neural networks …

The task of semantic segmentation holds a fundamental position in the field of computer
vision. Assigning a semantic label to each pixel in an image is a challenging task. In recent …

In this paper, we address the semantic segmentation task with a new context aggregation
scheme named object context, which focuses on enhancing the role of object information …

Change detection is a basic task of remote sensing image processing. The research
objective is to identify the change information of interest and filter out the irrelevant change …

In this paper, we address the scene segmentation task by capturing rich contextual
dependencies based on the self-attention mechanism. Unlike previous works that capture …

In humans, Attention is a core property of all perceptual and cognitive operations. Given our
limited ability to process competing sources, attention mechanisms select, modulate, and …

In this paper, we address the semantic segmentation task with a new context aggregation
scheme named\emph {object context}, which focuses on enhancing the role of object …

In this article, we propose a Dual Relation-aware Attention Network (DRANet) to handle the
task of scene segmentation. How to efficiently exploit context is essential for pixel-level …

Recent works have made great success in semantic segmentation by exploiting contextual
information in a local or global manner within individual image and supervising the model …

Recent works have made great progress in semantic segmentation by exploiting richer
context, most of which are designed from a spatial perspective. In contrast to previous works …