May 14, 2024, 4:47 a.m. | Jiahao Qin, Yitao Xu, Zong Lu, Xiaojun Zhang

cs.CV updates on

arXiv:2306.16950v2 Announce Type: replace
Abstract: Feature alignment is the primary means of fusing multimodal data. We propose a feature alignment method that fully fuses multimodal information, which stepwise shifts and expands feature information from different modalities to have a consistent representation in a feature space. The proposed method can robustly capture high-level interactions between features of different modalities, thus significantly improving the performance of multimodal learning. We also show that the proposed method outperforms other popular multimodal schemes on multiple …

abstract alignment arxiv consistent data feature fusion global guidance information interactions multimodal multimodal data replace representation space type

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