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Author (up) Ruben Tito; Dimosthenis Karatzas; Ernest Valveny
Title Document Collection Visual Question Answering Type Conference Article
Year 2021 Publication 16th International Conference on Document Analysis and Recognition Abbreviated Journal
Volume 12822 Issue Pages 778-792
Keywords Document collection; Visual Question Answering
Abstract Current tasks and methods in Document Understanding aims to process documents as single elements. However, documents are usually organized in collections (historical records, purchase invoices), that provide context useful for their interpretation. To address this problem, we introduce Document Collection Visual Question Answering (DocCVQA) a new dataset and related task, where questions are posed over a whole collection of document images and the goal is not only to provide the answer to the given question, but also to retrieve the set of documents that contain the information needed to infer the answer. Along with the dataset we propose a new evaluation metric and baselines which provide further insights to the new dataset and task.
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Notes DAG; 600.121 Approved no
Call Number Admin @ si @ TKV2021 Serial 3622
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