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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence, 35 / No. 4: AAAI-21 Technical Tracks 4

Efficient Object-Level Visual Context Modeling for Multimodal Machine Translation: Masking Irrelevant Objects Helps Grounding

February 1, 2023

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Authors

Dexin Wang

Tianjin University


Deyi Xiong

Tianjin University


DOI:

10.1609/aaai.v35i4.16376


Abstract:

Visual context provides grounding information for multimodal machine translation (MMT). However, previous MMT models and probing studies on visual features suggest that visual information is less explored in MMT as it is often redundant to textual information. In this paper, we propose an Object-level Visual Context modeling framework (OVC) to efficiently capture and explore visual information for multimodal machine translation. With detected objects, the proposed OVC encourages MMT to ground translation on desirable visual objects by masking irrelevant objects in the visual modality. We equip the proposed with an additional object-masking loss to achieve this goal. The object-masking loss is estimated according to the similarity between masked objects and the source texts so as to encourage masking source-irrelevant objects. Additionally, in order to generate vision-consistent target words, we further propose a vision-weighted translation loss for OVC. Experiments on MMT datasets demonstrate that the proposed OVC model outperforms state-of-the-art MMT models and analyses show that masking irrelevant objects helps grounding in MMT.

Topics: AAAI

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HOW TO CITE:

Dexin Wang||Deyi Xiong Efficient Object-Level Visual Context Modeling for Multimodal Machine Translation: Masking Irrelevant Objects Helps Grounding Proceedings of the AAAI Conference on Artificial Intelligence (2021) 2720-2728.

Dexin Wang||Deyi Xiong Efficient Object-Level Visual Context Modeling for Multimodal Machine Translation: Masking Irrelevant Objects Helps Grounding AAAI 2021, 2720-2728.

Dexin Wang||Deyi Xiong (2021). Efficient Object-Level Visual Context Modeling for Multimodal Machine Translation: Masking Irrelevant Objects Helps Grounding. Proceedings of the AAAI Conference on Artificial Intelligence, 2720-2728.

Dexin Wang||Deyi Xiong. Efficient Object-Level Visual Context Modeling for Multimodal Machine Translation: Masking Irrelevant Objects Helps Grounding. Proceedings of the AAAI Conference on Artificial Intelligence 2021 p.2720-2728.

Dexin Wang||Deyi Xiong. 2021. Efficient Object-Level Visual Context Modeling for Multimodal Machine Translation: Masking Irrelevant Objects Helps Grounding. "Proceedings of the AAAI Conference on Artificial Intelligence". 2720-2728.

Dexin Wang||Deyi Xiong. (2021) "Efficient Object-Level Visual Context Modeling for Multimodal Machine Translation: Masking Irrelevant Objects Helps Grounding", Proceedings of the AAAI Conference on Artificial Intelligence, p.2720-2728

Dexin Wang||Deyi Xiong, "Efficient Object-Level Visual Context Modeling for Multimodal Machine Translation: Masking Irrelevant Objects Helps Grounding", AAAI, p.2720-2728, 2021.

Dexin Wang||Deyi Xiong. "Efficient Object-Level Visual Context Modeling for Multimodal Machine Translation: Masking Irrelevant Objects Helps Grounding". Proceedings of the AAAI Conference on Artificial Intelligence, 2021, p.2720-2728.

Dexin Wang||Deyi Xiong. "Efficient Object-Level Visual Context Modeling for Multimodal Machine Translation: Masking Irrelevant Objects Helps Grounding". Proceedings of the AAAI Conference on Artificial Intelligence, (2021): 2720-2728.

Dexin Wang||Deyi Xiong. Efficient Object-Level Visual Context Modeling for Multimodal Machine Translation: Masking Irrelevant Objects Helps Grounding. AAAI[Internet]. 2021[cited 2023]; 2720-2728.


ISSN: 2374-3468


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