跨通道融合Mamba模块(CMFM) 经过LN(Layer Normalization)层进行标准化处理,以确保特征的稳定性,标准化后的特征首先通过线性变换(Linear)层以降低维度或调整特征的分布,然后进入深度卷积(Dw-Conv)层,这一层用于增强特征的局部信息,使得在空间域上对重要细节进行进一步提取,将融合后的特征输入到 ES2D 模块中,ES2D 是一...
Mamba. 自从Mamba [8] 被提出用于自然语言处理(NLP)领域的线性时间序列建模以来,它已被迅速扩展应用于各种计算机视觉任务中。Vmamba [21] 根据图像特征引入了一种四向扫描算法,并构建了一个基于Mamba的视觉基础网络,它在目标检测、目标分割和目标跟踪方面的性能优于Swin Transformer。VM-UNet [25] 在基于UNet框架和...
与现有的融合方法不同,作者构建了Fusion-Mamba模块,用于在隐空间中对不同模态进行对齐,从而显著提升目标检测性能,最高可达5.9%。本文提出了一种新颖的Fusion-Mamba方法,用于跨模态目标检测任务。该方法通过State Space Channel Swapping (SSCS)模块和Dual State Space Fusion (DSSF)模块,实现了多模态特征的有效融合。...
FusionMamba has yielded state-of-the-art (SOTA) performance across various multimodal medical image fusion tasks (CT-MRI, PET-MRI, SPECT-MRI), infrared and visible image fusion task (IR-VIS) and multimodal biomedical image fusion dataset (GFP-PC), which is proved that our model has ...
conda create -n FusionMamba python=3.8 conda activate FusionMamba pip install torch==1.13.0 torchvision==0.14.0 torchaudio==0.13.0 --extra-index-urlhttps://download.pytorch.org/whl/cu117 pip install packaging pip install timm==0.4.12 ...
Xie et al. Visual Intelligence (2024) 2:37 https://doi.org/10.1007/s44267-024-00072-9 Visual Intelligence RESEARCH Open Access FusionMamba: dynamic feature enhancement for multimodal image fusion with Mamba Xinyu Xie1,2, Yawen Cui3, Tao Tan2, Xubin Zheng1 and Zitong Yu1* Abstract ...
FusionMamba: Dynamic Feature Enhancement for Multimodal Image Fusion with Mamba - FusionMamba/logger.py at main · millieXie/FusionMamba
In this paper, we propose FusionMamba, a novel dynamic feature enhancement method for multimodal image fusion with Mamba. Specifically, we devise an improved efficient Mamba model for image fusion, integrating efficient visual state space model with dynamic convolution and channel attention. This ...
FusionMamba: Dynamic Feature Enhancement for Multimodal Image Fusion with Mamba Specifically, we devise an improved efficient Mamba model for image fusion, integrating efficient visual state space model with dynamic convolution and channel attention. This refined model not only upholds the performance of ...
FusionMamba好像进一步提升了全局能力! 多模态图像融合旨在从不同的模态中整合信息,以创建具有全面信息和详细纹理的单张图像。然而,基于卷积神经网络融合模型在捕捉全局图像特征方面存在局限性,这是由于它们侧重于局部卷积操作。尽管基于Transformer的模型在全球特征建模方面表现出色,但它们却面临着由二次复杂度引起的计算挑战...