论文:https://arxiv.org/abs/2103.04286代码:https://github.com/hli1221/imagefusion-rfn-nest 如有侵权请联系博主 介绍 关键词 可学习的融合网络 两阶段训练 新颖的有效的损失函数 简单介绍 一篇2021年发表的论文,论文作者是我们熟悉的DenseFuse的作者。
【读论文】RFN-Nest: An end-to-end residual fusion network for infrared and visible images 介绍 关键词 简单介绍 网络结构 RFN 融合网络 编码器 解码器 训练 训练自动编码器网络 损失函数 训练RFN 损失函数 实验 个人总结 参考 论文:https://arxiv.org/abs/2103.04286 代码:https://github.com/hli1221/im...
The code of our fusion method is available at https://github.com/hli1221/imagefusion-rfn-nest. 中文翻译: RFN-Nest:用于红外和可见图像的端到端残差融合网络 在图像融合领域,基于深度学习的融合方法的设计远非常规。它始终是特定于融合任务的,因此需要仔细考虑。设计中最困难的部分是选择适当的策略来为...
data sets show that, compared with the existing methods, our end-to-end fusion network delivers a better performance than the state-of-the-art methods in both subjective and objective evaluation. The code of our fusion method is available athttps://github.com/hli1221/imagefusion-rfn-nest. ...