High-resolution images have a wide range of applications in image compression, remote
sensing, medical imaging, public safety, and other fields. The primary objective of super …

In recent years, various neural network architectures for computer vision have been devised,
such as the visual transformer and multilayer perceptron (MLP). A transformer based on an …

Semantic segmentation is a dense pixel prediction task, and its accuracy depends on the
extraction of long-range contextual knowledge and refinement of segmentation boundaries …

Image Quality Assessment (IQA) is a fundamental task in computer vision that has witnessed
remarkable progress with deep neural networks. Inspired by the characteristics of the human …

Crowd counting is a fundamental and challenging task that requires rich information to
generate a pixel-level crowd density map. Additionally, the development of thermal sensing …

Understanding urban scenes is a fundamental capability required of intelligent vehicles.
Depth cues provide useful geometric information for semantic segmentation, thus …

Rail surface defect detection for traffic safety has received considerable attention. With the
development of deep learning, numerous methods for combining RGB and depth …

Infrared and visible image fusion, which highlights radiometric and detailed texture
information and completely and accurately describes objects, is a long-standing and well …

Insufficient image spatial resolution is a serious limitation in many practical scenarios,
especially when acquiring images at a finer scale is infeasible or brings higher costs. This is …

Research in psychology demonstrates that visual features and semantic content can convey
various emotions. Furthermore, studies have proved that image emotion and aesthetics are …