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English(EN) ConFusion: Continuous Fusion Space Learning for Fine-Grained Controllable Infrared and Visible Image Fusion

ConFusion框架实现细粒度可控的红外-可见光图像融合

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了ConFusion，一个用于细粒度可控红外与可见光图像融合的新框架。该方法使用高斯条件空间感知调制学习连续融合空间，从而能够灵活地整合热信息和结构信息。ConFusion采用双分支架构来解耦表示，并利用多模态大语言模型将用户意图解释为调制变量，以实现精确的图像融合。实验表明，ConFusion在融合质量和下游任务性能方面均优于现有方法。 AI

影响 通过利用大语言模型进行控制，为下游应用实现更精确、更具适应性的图像融合。

排序理由 该条目描述了一篇关于新型图像融合框架的最新研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 Hugging Face Daily Papers 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

ConFusion框架实现细粒度可控的红外-可见光图像融合

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该条目描述了一篇关于新型图像融合框架的最新研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. Hugging Face Daily Papers TIER_1 English(EN) ·

    ConFusion：用于细粒度可控红外与可见光图像融合的连续融合空间学习

    Controllable infrared-visible image fusion aims to integrate complementary thermal and structural information with flexible region-aware modulation, producing fused images that adapt to diverse user requirements and downstream tasks. However, existing methods typically rely on pr…

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