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Linguistic style is an essential part of written communication, with the power to affect both clarity and attractiveness. With recent advances in vision and language, we can start to tackle the problem of generating image captions that are both visually grounded and appropriately styled. Existing approaches either require styled training captions aligned to images or generate captions with low relevance. We develop a model that learns to generate visually relevant styled captions from a largedoi:10.1109/cvpr.2018.00896 dblp:conf/cvpr/MathewsXH18 fatcat:xsd2zvxz3jdclk25q6c2jdaiz4