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Images and text in advertisements interact in complex, non-literal ways. Thetwo channels are usually complementary, with each channel telling a differentpart of the story. Current approaches, such as image captioning methods, onlyexamine literal, redundant relationships, where image and text show exactly thesame content. To understand more complex relationships, we first collect adataset of advertisement interpretations for whether the image and slogan inthe same visual advertisement form a parallel (conveying the same messagewithout literally saying the same thing) or non-parallel relationship, with thehelp of workers recruited on Amazon Mechanical Turk. We develop a variety offeatures that capture the creativity of images and the specificity or ambiguityof text, as well as methods that analyze the semantics within and acrosschannels. We show that our method outperforms standard image-text alignmentapproaches on predicting the parallel/non-parallel relationship between imageand text.

Equal But Not The Same: Understanding the Implicit Relationship Between Persuasive Images and Text