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

新的ConFusion框架实现了对图像融合的细粒度控制

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了ConFusion，一种用于可控红外与可见光图像融合的新框架。该方法通过学习连续融合空间来解决现有方法的局限性，从而实现对融合图像进行细粒度、实例级别的调制。ConFusion利用双分支架构和高斯条件空间感知调制来解耦表示并增强语义一致性。该框架可以从多模态大语言模型解析用户意图来指导融合过程，在融合质量和下游任务方面取得了最先进的性能。 AI

影响 这项研究可能为各种应用带来更具适应性和更精确的图像处理工具。

排序理由 该集群包含一篇详细介绍新图像融合方法的学术论文。[lever_c_demoted from research: ic=1 ai=0.7]

在 arXiv cs.CV 阅读 →

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

新的ConFusion框架实现了对图像融合的细粒度控制

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该集群包含一篇详细介绍新图像融合方法的学术论文。[lever_c_demoted from research: ic=1 ai=0.7]
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报道来源 [1]

  1. arXiv cs.CV TIER_1 English(EN) · Guo Yurong, He Yufei, Li Yonghao, Chang Dongliang, Zhang Ke, Ma Zhanyu ·

    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

    arXiv:2607.23600v1 Announce Type: new Abstract: 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…

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