MAF: Multimodal Alignment Framework for Weakly-Supervised Phrase Grounding (2020.emnlp-main)
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| Challenge: | Existing work on phrase localization uses caption-image datasets as weak supervision . existing work on supervised phrase localisation uses a large-scale annotated dataset . |
| Approach: | They develop a multimodal alignment framework to leverage more widely available caption-image datasets to model phrase relevance. |
| Outcome: | The proposed model improves on the widely-adopted Flickr30k dataset . it also improves the previous best unsupervised result by 5.56% . |
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