Papers with Microsoft-COCO

2 papers
Aligning Multilingual Word Embeddings for Cross-Modal Retrieval Task (D19-64)

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Challenge: Existing methods to learn multimodal multilingual embeddings for text and image retrieval tasks are limited to English.
Approach: They propose a new approach to learn multimodal multilingual embeddings for matching images and captions in two languages by combing two existing objective functions and adapting alignment between existing languages.
Outcome: The proposed model achieves state-of-the-art in retrieval and caption-caption tasks while adapting existing language alignments.
Aligning Multilingual Word Embeddings for Cross-Modal Retrieval Task (D19-66)

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Challenge: Existing methods to learn multimodal multilingual embeddings for text and image retrieval tasks are limited to English.
Approach: They propose a new approach to learn multimodal multilingual embeddings for matching images and captions in two languages by combing two existing objective functions and adapting alignment between existing languages.
Outcome: The proposed model achieves state-of-the-art in retrieval and caption-caption tasks while adapting existing language alignments.

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