The goal of semantic segmentation is to segment the input image according to semantic
information and predict the semantic category of each pixel from a given label set. With the …

Semantic segmentation is a challenging task in computer vision. In recent years, the
performance of semantic segmentation has been greatly improved by using deep learning …

This paper introduces an extremely efficient CNN architecture named DFANet for semantic
segmentation under resource constraints. Our proposed network starts from a single …

Semantic image segmentation (SiS) plays a fundamental role in a broad variety of computer
vision applications, providing key information for the global understanding of an image. This …

Deep Convolutional Neural Networks (DCNNs) have recently shown outstanding
performance in semantic image segmentation. However, state-of-the-art DCNN-based …

Capturing accurate multiscale semantic information from the images is of great importance
for high-quality semantic segmentation. Over the past years, a large number of methods …

Semantic segmentation for urban remote sensing images is one of the most-crucial tasks in
the field of remote sensing. Remote sensing images contain rich information on ground …

Semantic image segmentation for autonomous driving is a challenging task due to its
requirement for both effectiveness and efficiency. Recent developments in deep learning …

The encoder–decoder structure has been introduced into semantic segmentation to improve
the spatial accuracy of the network by fusing high-and low-level feature maps. However …

Real-time semantic segmentation plays a significant role in industry applications, such as
autonomous driving, robotics and so on. It is a challenging task as both efficiency and …