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2015
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Image2Emoji: Zero-shot Emoji Prediction for Visual Media

4 years 6 months ago
Image2Emoji: Zero-shot Emoji Prediction for Visual Media
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.
Spencer Cappallo, Thomas Mensink, Cees G. M. Snoek
Added 14 Apr 2016
Updated 14 Apr 2016
Type Journal
Year 2015
Where MM
Authors Spencer Cappallo, Thomas Mensink, Cees G. M. Snoek
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