We resort to plain vision transformers with about 100M and make the first attempt to propose large vision models customized for RS tasks and propose a new rotated varied-size window attention (RVSA) ...

The Transformers repository provides a comprehensive implementation of the Transformer architecture, a groundbreaking model that has revolutionized both Natural Language Processing (NLP) and Computer ...

Transformer obtains the powerful ability of long-range context modeling, but the computation complexity of conventional Transformer is quadratic to feature map size. For dense prediction tasks with ...

Transformer-based language models process text by analyzing word relationships rather than reading in order. They use attention mechanisms to focus on keywords, but handling longer text is challenging ...

Abstract: The quadratic increase in computational complexity caused by global receptive fields has been a persistent challenge when applying Transformer-based methods in remote sensing image ...

To address these challenges, this work introduces a novel Cross-Attention and Multi-Correlation Aided Transformer (CAMCFormer) FSOD framework tailored for global feature representation and ...