The attention module is the key component in Transformers. While the global attention
mechanism offers high expressiveness, its excessive computational cost restricts its …

Complex physicochemical environmental effects result in the underwater species images'
highly intricate and diverse backgrounds, which poses significant challenges for identifying …

Large models based on the Transformer architecture play increasingly vital roles in artificial
intelligence, particularly within the realms of natural language processing (NLP) and …

Zero-shot 6D object pose estimation involves the detection of novel objects with their 6D
poses in cluttered scenes presenting significant challenges for model generalizability …

This paper identifies significant redundancy in the query-key interactions within self-attention
mechanisms of diffusion transformer models, particularly during the early stages of …

Abstract Although Vision Transformer (ViT) has achieved significant success in computer
vision it does not perform well in dense prediction tasks due to the lack of inner-patch …

Hyperbolic geometry have shown significant potential in modeling complex structured data,
particularly those with underlying tree-like and hierarchical structures. Despite the …

In pediatric cardiology, the accurate and immediate assessment of cardiac function through
echocardiography is crucial since it can determine whether urgent intervention is required in …

In image fusion tasks, images from different sources possess distinct characteristics. This
has driven the development of numerous methods to explore better ways of fusing them …

Abstract Multimodal Large Language Models (MLLMs) have demonstrated remarkable
comprehension and reasoning capabilities with complex language and visual data. These …