March 26, 2024, 4:47 a.m. | Xunpeng Yi, Han Xu, Hao Zhang, Linfeng Tang, Jiayi Ma

cs.CV updates on arXiv.org arxiv.org

arXiv:2403.16387v1 Announce Type: new
Abstract: Image fusion aims to combine information from different source images to create a comprehensively representative image. Existing fusion methods are typically helpless in dealing with degradations in low-quality source images and non-interactive to multiple subjective and objective needs. To solve them, we introduce a novel approach that leverages semantic text guidance image fusion model for degradation-aware and interactive image fusion task, termed as Text-IF. It innovatively extends the classical image fusion to the text guided …

arxiv cs.cv fusion guidance image interactive semantic text type

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