Unleashing the Power of Text: Text-Guided Flow Matching for Image Fusion under Complex Degradations
Infrared-visible image fusion under realistic degradation scenarios is a challenging task, as degradations not only cause a loss of reliable modality-specific information in observed images but also hinder the fusion process. Recent studies indicate that text can provide prior information about degradation characteristics, complementing the limited evidence available from corrupted input images and facilitating fusion. However, existing methods typically inject fixed global text representations into visual features, making it difficult for textual guidance to adapt to spatially varying degradations, local structures, and thermal saliency. To this end, we propose TGFusion, a text-guided la...
| Authors | Axi Niu, Jieheng Li, Kang Zhang et al. |
|---|---|
| Primary category | cs.CV |
| Published | 1 August 2026 |
| Last updated at source | 1 August 2026 |
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