Graph Neural Networks (GNNs) have gained momentum in graph representation learning
and boosted the state of the art in a variety of areas, such as data mining (\emph {eg,} social …

A knowledge graph (KG), a special form of semantic network, integrates fragmentary data
into a graph to support knowledge processing and reasoning. KG quality control is important …

Open-world object detection, as a more general and challenging goal, aims to recognize
and localize objects described by arbitrary category names. The recent work GLIP …

Scene graphs are powerful representations that parse images into their abstract semantic
elements, ie, objects and their interactions, which facilitates visual comprehension and …

Abstract Open Set Domain Adaptation (OSDA) transfers the model from a label-rich domain
to a label-free one containing novel-class samples. Existing OSDA works overlook abundant …

Ship detection plays a pivotal role in efficient marine monitoring, port management, and safe
navigation. However, the development of ship detection techniques is vastly behind other …

Since the propagation of deep neural networks results in the loss of detailed feature
information, the performance of most object detection methods is limited due to their …

Visual Emotion Analysis (VEA) aims at finding out how people feel emotionally towards
different visual stimuli, which has attracted great attention recently with the prevalence of …

Mammogram mass detection is of great clinical significance due to its high proportion in
breast cancers. The information from cross views (ie, mediolateral oblique and cranio …

Owing to the rich emerging multimedia applications and services in the past decade, super
large amount of multimedia data has been produced for the purpose of advanced research …