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Detecting Persuasive Atypicality by Modeling Contextual Compatibility

2021-01-01ICCV 2021Code Available0· sign in to hype

Meiqi Guo, Rebecca Hwa, Adriana Kovashka

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Abstract

We propose a new approach to detect atypicality in persuasive imagery. Unlike atypicality which has been studied in prior work, persuasive atypicality has a particular purpose to convey meaning, and relies on understanding the common-sense spatial relations of objects. We propose a self-supervised attention-based technique which captures contextual compatibility, and models spatial relations in a precise manner. We further experiment with capturing common sense through the semantics of co-occurring object classes. We verify our approach on a dataset of atypicality in visual advertisements, as well as a second dataset capturing atypicality that has no persuasive intent.

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