Papers by Silpa Vadakkeeveetil Sreelatha

1 papers
Understanding Advertisements with BERT (2020.acl-main)

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Challenge: Recent results have shown that the embedded scene-text in the image holds a vital cue for this task.
Approach: They propose to use the embedded scene-text as a cue for a sentence-pair classification task based on CVPR 2018 challenge dataset on advertisement understanding to rank valid and negatively sampled invalid interpretations of an image.
Outcome: The proposed model achieves 89.69% accuracy, an improvement of 4.7% on the previous model.

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