Feature Fusion

MFT-GAN: A Multi-Scale Feature Guided Transformer Network for Unsupervised Hyperspectral Pan-Sharpening

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MFT-GAN: A Multi-Scale Feature Guided Transformer Network for Unsupervised Hyperspectral Pan-Sharpening

Click the “ReadingPapers” card below to get daily interpretations of top journal papers. Paper Information Abstract Unsupervised learning, which learns data distribution without labeled samples, is a very promising method to solve the challenging task of hyperspectral pan-sharpening. Inspired by this, we introduce an innovative Generative Adversarial Network framework (named MFT-GAN), which integrates transformer networks … Read more

Attention Mechanism in CV: FFM and ARM Modules in BiSeNet

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Attention Mechanism in CV: FFM and ARM Modules in BiSeNet

BiSeNet, which utilizes attention mechanisms in semantic segmentation, has two modules: the FFM module and the ARM module. Its implementation is quite straightforward, but the author has a deep understanding of the attention mechanism and proposes a novel feature fusion method through the FFM module. One Introduction Semiotic segmentation requires rich spatial information and a … Read more