Multimodal Fusion Generative Adversarial Network for Image Synthesis

Text-to-image synthesis has advanced significantly; however, a crucial limitation persists: textual descriptions often neglect essential background details, leading to blurred backgrounds and diminished image quality. To address this, we propose a multimodal fusion framework that integrates informat...

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Veröffentlicht in:	IEEE signal processing letters 2024, Vol.31, p.1865-1869
Hauptverfasser:	Zhao, Liang, Hu, Qinghao, Li, Xiaoyuan, Zhao, Jingyuan
Format:	Artikel
Sprache:	eng
Schlagworte:	Attention mechanisms Birds Datasets Descriptions Feature fusion Feature maps generative adversarial network Generative adversarial networks Image quality Image synthesis Mathematical models Semantics Synthesis text-to-image synthesis
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