MetaEarth-MM unifies multi-modal remote sensing image generation and any-to-any translation across five modalities via scene-centered joint modeling on the new EarthMM dataset.
Fsim: A feature similarity index for image quality assessment
2 Pith papers cite this work. Polarity classification is still indexing.
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TEA is a new targeted adversarial attack that incorporates edge information from the target image to reduce query count and improve performance in low-query black-box hard-label settings.
citing papers explorer
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MetaEarth-MM: Unified Multimodal Remote Sensing Image Generation with Scene-centered Joint Modeling
MetaEarth-MM unifies multi-modal remote sensing image generation and any-to-any translation across five modalities via scene-centered joint modeling on the new EarthMM dataset.
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Accelerating Targeted Hard-Label Adversarial Attacks in Low-Query Black-Box Settings
TEA is a new targeted adversarial attack that incorporates edge information from the target image to reduce query count and improve performance in low-query black-box hard-label settings.