Semantic segmentation is a critical component for street understanding task in autonomous
driving field. Existing various methods either focus on constructing the object's inner …

Transformer-based models have been widely demonstrated to be successful in computer
vision tasks by modeling long-range dependencies and capturing global representations …

Night-Time Scene Parsing (NTSP) is essential to many vision applications, especially for
autonomous driving. Most of the existing methods are proposed for day-time scene parsing …

Cloud detection is critical in remote sensing image processing, and convolutional neural
networks (CNNs) have significantly advanced this field. However, traditional CNNs primarily …

Defect semantic segmentation is a pixel-level inspection technique to guarantee the quality
of various products. It can obtain the precise location of defects by assigning a class label to …

This paper focuses on the high-resolution (HR) remote sensing images semantic
segmentation task, whose goal is to predict semantic labels in a pixel-wise manner. Due to …

Intelligent traffic systems represent one of the crucial domains in today's world, aiming to
enhance traffic management efficiency and road safety. However, current intelligent traffic …

Abstract Domain generalization semantic segmentation methods aim to generalize well on
out-of-distribution scenes, which is crucial for real-world applications. Recent works focus on …

Medical image segmentation is indispensable for diagnosis and prognosis of many
diseases. To improve the segmentation performance, this study proposes a new 2D body …

Over the past few years, there have been significant advancements in deep learning
technology, leading to remarkable progress in the field of image analysis. However, when it …