Learning-based image inpainting methods have made remarkable progress in recent years.
Nevertheless, these methods still suffer from issues such as blurring, artifacts, and …

Person search simultaneously detects and retrieves a query person from uncropped scene
images. Existing methods are either two-step or end-to-end. The former employs two …

The lifelong person re-identification (LRe-ID) model retrieves a person across multiple
cameras in continuous data streams and learns new coming datasets incrementally …

Deep learning, especially convolutional neural networks (CNNs) and Transformer
architectures, have become the focus of extensive research in medical image segmentation …

The goal of few-shot fine-grained image classification (FSFGIC) is to distinguish subordinate-
level categories with subtle visual differences such as the species of bird and models of car …

The deep vision sensing has been a practical tool in early disease detection, and this work
aims at an important branch of ocular disease recognition. Although a number of …

Continually learning to segment more and more types of image regions is a desired
capability for many intelligent systems. However, such continual semantic segmentation …

Partial discharge (PD) detection of cable terminals is crucial for the safe operation of the
traction power system in trains. However, similar PD signals in complex train‐operating …

Transformer 是一种基于自注意力机制的深度学习模型, 在计算机视觉中展现出巨大的潜力.
而在图像分类任务中, 关键的挑战是高效而准确地捕捉输入图片的局部和全局特征 …

Data augmentation is a crucial technique for expanding training datasets, effectively
alleviating the overfitting issue that arises from limited training data in deep learning models …