Skeleton-based zero-shot action recognition aims to recognize unknown human actions
based on the learned priors of the known skeleton-based actions and a semantic descriptor …

This paper provides a novel parsimonious yet efficient design for zero-shot learning (ZSL),
dubbed ParsNets, where we are interested in learning a composition of on-device friendly …

The human visual system can rapidly focus on prominent objects in complex scenes,
significantly enhancing information processing efficiency. Salient object detection (SOD) …

The task of multimodal image fusion aims to preserve the respective advantages of each
modality, such as the detailed texture information from visible light images and the salient …

RGB-D salient object detection (SOD) models based on a two-stream structure have
achieved good performance in single-object scenes. In multi-object scenes, there is an …

Zero-shot skeleton action recognition is a non-trivial task that requires robust unseen
generalization with prior knowledge from only seen classes and shared semantics. Existing …

Zero-shot learning has consistently yielded remarkable progress via modeling nuanced one-
to-one visual-attribute correlation. Existing studies resort to refining a uniform mapping …

Abstract Salient Object Detection (SOD) is a challenging task that aims to precisely identify
and segment the salient objects. However, existing SOD methods still face challenges in …

Underwater sonar image salient object detection (SOD) plays a crucial role in underwater
rescue and marine resource discovery. Although existing SOD methods have shown some …

Deep learning methods have shown promising results in camera-based object detection.
However, their effectiveness is significantly hindered in real-world scenes with poor …