Connecting text and visual modalities plays an essential role in generative intelligence. For
this reason, inspired by the success of large language models, significant research efforts …

Designing computationally efficient network architectures remains an ongoing necessity in
computer vision. In this paper, we adapt Mamba, a state-space language model, into …

In recent years, Transformers have become the de-facto architecture for sequence modeling
on text and multi-dimensional data, such as images and video. However, the use of self …

Vision Transformers (ViTs) have achieved remarkable success in computer vision tasks.
However, their potential in rotation-sensitive scenarios has not been fully explored, and this …

There has been significant progress in Masked Image Modeling (MIM). Existing MIM
methods can be broadly categorized into two groups based on the reconstruction target …

Object detection plays a crucial role in scene understanding and has extensive practical
applications. In the field of remote sensing object detection, both detection accuracy and …

Recently the advancement of self-supervised learning techniques like masked
autoencoders (MAE) has greatly influenced visual representation learning for images and …

A fundamental problem in learning robust and expressive visual representations lies in
efficiently estimating the spatial relationships of visual semantics throughout the entire …

Efficient feature extraction is a pivotal requirement for Deep Neural Network (DNN) models,
particularly in the realm of visual tasks where effective feature extraction relies on well …

Unmanned surface vehicles (USVs) are distinguished by their intelligence, compactness,
and absence of human casualties, making them a vital component of the maritime industry …