Semantic segmentation finds wide-ranging applications and stands as a crucial task in the
realm of computer vision. It holds significant implications for scene comprehension and …

Semantic segmentation is an advanced research topic in computer vision and can be
regarded as a fundamental technique for image understanding and analysis. However, most …

The convolutional neural network achieves excellent semantic segmentation results in
artificially annotated datasets with complex scenes. However, semantic segmentation …

Semantic segmentation is a typical problem in the field of machine vision. Convolutional
neural networks (CNNs)-based methods all have excellent performance in image semantic …

Transformer has excellent global expression ability. Recently, researchers have proposed
many Transformer-based image semantic segmentation networks, and most of them have …

Recent non-local self-attention methods have proven to be effective in capturing long-range
dependencies for semantic segmentation. These methods usually form a similarity map of …

Semantic scene segmentation has become an important application in computer vision and
is an essential part of intelligent transportation systems for complete scene understanding of …

The encoder-decoder structure has significantly improved performance in many vision tasks
by fusing low-level and high-level feature maps. However, this approach can hardly extract …

Semantic segmentation is used in many fields, and most fields not only require models with
high-quality predictions but also require real-time speed in the forward inference phase …

Semantic segmentation is a challenging task in computer vision which is widely used in
autonomous driving and scene understanding. State‐of‐the‐art semantic segmentation …