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Found 2 papers, 1 papers with code
A Corpus for Visual Question Answering Annotated with Frame Semantic Information
Visual Question Answering (VQA) has been widely explored as a computer vision problem, however enhancing VQA systems with linguistic information is necessary for tackling the complexity of the task.
Augmenting Visual Question Answering with Semantic Frame Information in a Multitask Learning Approach
Our first contribution is a new VQA dataset (imSituVQA) that we built by taking advantage of the imSitu annotations.
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