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- W1983440957 abstract "We present Image2Emoji, a multi-modal approach for generating emoji labels for an image in a zero-shot manner. Different from existing zero-shot image-to-text approaches, we exploit both image and textual media to learn a semantic embedding for the new task of emoji prediction. We propose that the widespread adoption of emoji suggests a semantic universality which is well-suited for interaction with visual media. We quantify the efficacy of our proposed model on the MSCOCO dataset, and demonstrate the value of visual, textual and multi-modal prediction of emoji. We conclude the paper with three examples of the application potential of emoji in the context of multimedia retrieval." @default.
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- W1983440957 date "2015-10-13" @default.
- W1983440957 modified "2023-10-17" @default.
- W1983440957 title "Image2Emoji" @default.
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- W1983440957 doi "https://doi.org/10.1145/2733373.2806335" @default.
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