AI RESEARCH
Rethinking Few-Shot Image Fusion: Granular Ball Priors Enable General-Purpose Deep Fusion
arXiv CS.LG
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ArXi:2504.08937v5 Announce Type: replace-cross In image fusion tasks, the absence of real fused images as supervision signals poses significant challenges for supervised learning. Existing deep learning methods typically address this issue either by designing handcrafted priors or by relying on large-scale datasets to learn model parameters. Different from previous approaches, this paper