论文假设是,在MMIF任务中,两个模态的输入特征在低频时是相关的,代表模态共享的信息,而高频特征是不相关的,代表各自模态的独特特征。 CDDFuse包含四个模块,即双分支编码器用于特征提取和分解,解码器用于重建原始图像(在训练阶段I)或生成融合图像(在训练阶段II),以及基础/细节融合层分别用于融合不同频率的特征。 训练...
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 Timoft…
进一步,提出了相关驱动损失(correlation-driven loss),基于嵌入信息(embedded information)使低频特征相关,而高频特征不相关。 然后,基于LT的全局融合层和基于INN的局部融合层输出融合图像。 贡献: 大量实验表明,CDDFuse在红外与可见光及医学图像融合性能卓越。 此外,证明了CDDFuse在统一的benchmark中,在红外可见光语义...
Correlation-driven chiral superconductivity and chiral spin order in doped kagome latticeCondensed Matter - Strongly Correlated ElectronsWe study the electronic instabilities of the Hubbard model in the 1/6 hole-doped Kagome lattice using the variational cluster approach. The 1/6 hole doping is unique...
is a well-known example of strong electron correlation existing in heavy-electron compounds. The Kondo-mediated topological phases of matter have been studied in the context of topological Kondo insulators6,7,8and topological Kondo semi-metals9,10, where the topological properties are driven either ...
Correlation-driven neural network model (CDNN) There are many Machine Learning (ML) algorithms, such as the linear ML algorithms, nonlinear ML algorithms and ensemble ML algorithms that have been commonly used in the previous literature72,74. It has been extensively reported that the creep-fatigue...
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...
Electronic correlation is of fundamental importance to high temperature superconductivity. While the low energy electronic states in cuprates are dominantly affected by correlation effects across the phase diagram, observation of correlation-driven changes in fermiology amongst the iron-based superconductors ...
CORN: Correlation-Driven Nonparametric Learning Approach for Portfolio Selection -- an Online Appendix 来自 arXiv.org 喜欢 0 阅读量: 104 作者:B Li,D Huang,Hoi, Steven C. H. 摘要: This appendix proves CORN's universal consistency. One of Bin's PhD thesis examiner (Special thanks to ...
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...