CDDFuse: Correlation-Driven Dual-Branch Feature Decomposition for Multi-Modality Image Fusion 会议及时间 CVPR2023 主要内容 为了解决建模跨模态特征和分解期望模态特有和模态共有特征的挑战,本文提出了一种用于多模态图像融合的双分支Transformer-CNN架构CDDFuse,通过结合Transformer和CNN的优势,实现了多任务多模态图像...
论文题目:《CDDFuse: Correlation-Driven Dual-Branch Feature Decomposition for Multi-Modality Image Fusion》 作者:Zixiang Zhao, Haowen Bai, Jiangshe Zhang,Yulun Zhang,Shuang Xu, Zudi Lin,Radu Timofte, Luc Van Gool 单位:西安交通大学、苏黎世联邦理工学院、西北工业大学、哈佛大学、维尔茨堡大学 会议:CVPR...
# 图像融合论文阅读:CDDFuse: Correlation-Driven Dual-Branch Feature Decomposition for Multi-Modality Image Fusion @inproceedings{zhao2023cddfuse, title={Cddfuse: Correlation-driven dual-branch fea…
To this end, we proposed the Correlation-Driven feature Decomposition Fusion (CDDFuse) model, where modality- specific and modality-shared feature extractions are realized by a dual-branch encoder, with the fused image reconstructed by the decoder...
CDDFuse: Correlation-Driven Dual-Branch Feature Decomposition for Multi-Modality Image Fusion SUPPLEMENTARY MATERIALS Zixiang Zhao1,2 Haowen Bai1 Jiangshe Zhang1* Yulun Zhang2 Shuang Xu3,4 Zudi Lin5 Radu Timofte2,6 Luc Van Gool2 1 Xi'an Jiaotong University 2 Computer Visi...
@InProceedings{Zhao_2023_CVPR, author = {Zhao, Zixiang and Bai, Haowen and Zhang, Jiangshe and Zhang, Yulun and Xu, Shuang and Lin, Zudi and Timofte, Radu and Van Gool, Luc}, title = {CDDFuse: Correlation-Driven Dual-Branch Feature Decomposition for Multi-Modality Image Fusion}, book...
本文的研究目的是提出一种新颖的多模态图像融合网络,名为CDDFuse(Correlation-Driven Dual-Branch Feature Decomposition Fusion),用于处理不同模态图像融合的挑战。具体来说,CDDFuse旨在生成融合图像,同时保留不同模态的优势,例如在红外图像中保留热辐射信息和在可见光图像中保留详细的纹理信息。该网络通过建模跨模态特征...