While semantic segmentation has seen tremendous improvements in the past, there are still
significant labeling efforts necessary and the problem of limited generalization to classes …

Deep learning based fusion mechanisms have achieved sophisticated performance in the
field of image fusion. However, most existing approaches focus on learning global and local …

Outdoor images taken in haze usually exhibit contrast reduction, color distortion, and detail
loss. Removing the haze from a given image is a tough issue owing to its highly ill-posed …

The application of intelligent image recognition technology in life is more and more
extensive, especially in the field of computer and multimedia, the research of machine vision …

Recently, class incremental semantic segmentation (CISS) towards the practical open-world
setting has attracted increasing research interest, which is mainly challenged by the well …

Semantic segmentation of remote sensing (RS) images plays a vital role in a variety of fields,
including urban planning, natural disaster monitoring, and land resource management. Due …

How to fuse low-level and high-level features effectively is crucial to improving the accuracy
of medical image segmentation. Most CNN-based segmentation models on this topic usually …

Adaptive filtering algorithm (FIR) is a design method of adaptive variable target tracking
system based on probability density distribution model. The algorithm realizes the target …

A 3D mesh is a popular representation of 3D shapes. For mesh analysis tasks, one typical
method is to map 3D mesh data into 1D sequence data with random walk sampling …

Novel view synthesis aims at rendering any posed images from sparse observations of the
scene. Recently, neural radiance fields (NeRF) have demonstrated their effectiveness in …