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• W2963496089 abstract "In this paper we propose a model to learn multimodal multilingual representations for matching images and sentences in different languages, with the aim of advancing multilingual versions of image search and image understanding. Our model learns a common representation for images and their descriptions in two different languages (which need not be parallel) by considering the image as a pivot between two languages. We introduce a new pairwise ranking loss function which can handle both symmetric and asymmetric similarity between the two modalities. We evaluate our models on image-description ranking for German and English, and on semantic textual similarity of image descriptions in English. In both cases we achieve state-of-the-art performance." @default.
• W2963496089 created "2019-07-30" @default.
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• W2963496089 date "2017-01-01" @default.
• W2963496089 modified "2023-10-05" @default.
• W2963496089 title "Image Pivoting for Learning Multilingual Multimodal Representations" @default.
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• W2963496089 doi "https://doi.org/10.18653/v1/d17-1303" @default.
• W2963496089 hasPublicationYear "2017" @default.
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