{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/visual-question-answering-datasets-algorithms","title":"Visual Question Answering: Datasets, Algorithms, and Future Challenges","arxiv_id":"1610.01465","date":"2016-10-05","proceeding":null,"authors":["Kushal Kafle","Christopher Kanan"],"abstract":"Visual Question Answering (VQA) is a recent problem in computer vision and\nnatural language processing that has garnered a large amount of interest from\nthe deep learning, computer vision, and natural language processing\ncommunities. In VQA, an algorithm needs to answer text-based questions about\nimages. Since the release of the first VQA dataset in 2014, additional datasets\nhave been released and many algorithms have been proposed. In this review, we\ncritically examine the current state of VQA in terms of problem formulation,\nexisting datasets, evaluation metrics, and algorithms. In particular, we\ndiscuss the limitations of current datasets with regard to their ability to\nproperly train and assess VQA algorithms. We then exhaustively review existing\nalgorithms for VQA. Finally, we discuss possible future directions for VQA and\nimage understanding research.","url_abs":"http://arxiv.org/abs/1610.01465v4","url_pdf":"http://arxiv.org/pdf/1610.01465v4.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"visual-question-answering-datasets-algorithms","repo_url":"https://github.com/andreiluca96/reversed-vqa","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"question-answering","task_name":"Question Answering"},{"task_slug":"visual-question-answering-1","task_name":"Visual Question Answering"},{"task_slug":"visual-question-answering","task_name":"Visual Question Answering (VQA)"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1610.01465","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}