A graph structure is a powerful mathematical abstraction, which can not only represent
information about individuals but also capture the interactions between individuals for …

The task of multi-label image recognition is to predict a set of object labels that present in an
image. As objects normally co-occur in an image, it is desirable to model the label …

Multi-label image recognition is a challenging computer vision task of practical use.
Progresses in this area, however, are often characterized by complicated methods, heavy …

Recent studies often exploit Graph Convolutional Network (GCN) to model label
dependencies to improve recognition accuracy for multi-label image recognition. However …

Recognizing multiple labels of images is a practical and challenging task, and significant
progress has been made by searching semantic-aware regions and modeling label …

Recognizing multiple labels of an image is a practical yet challenging task, and remarkable
progress has been achieved by searching for semantic regions and exploiting label …

Visual attention has become a popular and widely used component for image recognition.
Although various attention-based methods have been proposed and achieved relatively …

The simultaneous recognition of multiple objects in one image remains a challenging task,
spanning multiple events in the recognition field such as various object scales, inconsistent …

This paper proposes a novel deep architecture to address multi-label image recognition, a
fundamental and practical task towards general visual understanding. Current solutions for …

Prompt tuning has been employed as an efficient way to adapt large vision-language pre-
trained models (eg CLIP) to various downstream tasks in data-limited or label-limited …