Supervised Multimodal Bitransformers for Classifying Images and Text

Douwe Kiela; Suvrat Bhooshan; Hamed Firooz; Ethan Perez; Davide Testuggine

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arXiv · 1909.02950

Supervised Multimodal Bitransformers for Classifying Images and Text

Douwe Kiela·Suvrat Bhooshan·Hamed Firooz·Ethan Perez·Davide Testuggine

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Abstract

Self-supervised bidirectional transformer models such as BERT have led to dramatic improvements in a wide variety of textual classification tasks. The modern digital world is increasingly multimodal, however, and textual information is often accompanied by other modalities such as images. We introduce a supervised multimodal bitransformer model that fuses information from text and image encoders, and obtain state-of-the-art performance on various multimodal classification benchmark tasks, outperforming strong baselines, including on hard test sets specifically designed to measure multimodal performance.

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Douwe Kiela, Suvrat Bhooshan, Hamed Firooz, Ethan Perez, Davide Testuggine. 2019-09-06. Supervised Multimodal Bitransformers for Classifying Images and Text. https://arxiv.org/abs/1909.02950

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