Visual Question Answering Dataset for Bilingual Image Understanding: A Study of Cross-Lingual Transfer Using Attention Maps (C18-1)
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| Challenge: | Existing literature on visual question answering (VQA) focuses on English, but there are no datasets for other languages. |
| Approach: | They propose a cross-lingual method to make use of English annotation to improve Japanese VQA . they use attention maps generated from English questions to improve the task . |
| Outcome: | The proposed method performs better than using a monolingual corpus in Japanese than using monolingual ones. |
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| Challenge: | Existing studies on cross-lingual VQA have reported poor zero-shot transfer performance of current multilingual multimodal Transformers . lack of multilingual resources has hindered development and evaluation of VQA methods beyond the English language . |
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Translation Deserves Better: Analyzing Translation Artifacts in Cross-lingual Visual Question Answering (2024.findings-acl)
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ChaeHun Park, Koanho Lee, Hyesu Lim, Jaeseok Kim, Junmo Park, Yu-Jung Heo, Du-Seong Chang, Jaegul Choo
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Soravit Changpinyo, Linting Xue, Michal Yarom, Ashish Thapliyal, Idan Szpektor, Julien Amelot, Xi Chen, Radu Soricut
| Challenge: | Visual Question Answering (VQA) has been studied in the English language, but in other languages it would require a considerable amount of resources. |
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| Challenge: | Visual Question Answering (VQA) is a computer vision problem. |
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| Challenge: | Open-domain question answering aims to answer questions through text retrieval and reading comprehension . but, the success of these models relies on a massive volume of training data, which is not available in other languages . a new dataset aims at investigating cross-lingual OpenQA . |
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HaVQA: A Dataset for Visual Question Answering and Multimodal Research in Hausa Language (2023.findings-acl)
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A Unified Framework for Multilingual and Code-Mixed Visual Question Answering (2020.aacl-main)
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| Challenge: | Existing techniques for visual question answering focus on English questions, but many applications require a multilingual module. |
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Can We Learn Question, Answer, and Distractors All from an Image? A New Task for Multiple-choice Visual Question Answering (2024.lrec-main)
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| Challenge: | Existing studies focus on generating QADs from image and question, but a novel task is needed to generate meaningful questions, correct answers, and challenging distractors. |
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All You May Need for VQA are Image Captions (2022.naacl-main)
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| Challenge: | Visual Question Answering (VQA) has benefited from increasingly sophisticated models, but has not enjoyed the same level of engagement in terms of data creation. |
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