English(EN) RoES: Rotational Equivariant Selective-frequency Fusion for Multimodal Images

新型RoES网络采用选择性频率方法融合多模态图像

作者 PulseAugur 编辑部 · [1 个来源] · 2026-09-14 04:00

研究人员开发了RoES，一种用于融合多模态图像的新型网络，通过选择性地处理低频和高频分量。该方法使用可训练模块动态解耦这些频率，从而更好地保留独特信息。低频分量利用旋转等变的Mamba处理结构依赖性，而高频细节则使用基于极谱注意力的Dual-Fourier块进行细化。RoES在融合质量和下游目标检测任务中均展现出最先进的性能。 AI

影响这项研究推进了多模态图像融合技术，有望提高目标检测等下游AI任务的性能。

排序理由该集群包含一篇详细介绍图像融合新技术的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CV 阅读 →

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Newsworthiness bucket: Tool; 该集群包含一篇详细介绍图像融合新技术的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

arXiv cs.CV TIER_1 English(EN) · Jiabao Wang, Wenjian Liu, Yaoming Cai, Gengyu Zhang, Boyan Zhao, Zijia Zhang, Yao Ding, Xiaobo Liu · 2026-09-14 04:00

RoES：多模态图像的旋转等变选择性频率融合

arXiv:2609.12497v1 Announce Type: new Abstract: Infrared-visible image fusion facilitates robust multimodal perception by integrating complementary textural nuances from visible sensors with thermal signatures from infrared systems. Due to the task's inherently ill-posed nature, …

本文如何被排名

报道来源 [1]

RoES：多模态图像的旋转等变选择性频率融合

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