Visual Question Answering: A Survey on Techniques and Common Trends in Recent Literature

Ana Cláudia Akemi Matsuki de Faria, Felype de Castro Bastos, José Victor Nogueira Alves da Silva, Vitor Lopes Fabris, Valeska de Sousa Uchoa +2 more
5/18/2023
cs.CVcs.AIcs.LG

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Abstract

Visual Question Answering (VQA) is an emerging area of interest for researches, being a recent problem in natural language processing and image prediction. In this area, an algorithm needs to answer questions about certain images. As of the writing of this survey, 25 recent studies were analyzed. Besides, 6 datasets were analyzed and provided their link to download. In this work, several recent pieces of research in this area were investigated and a deeper analysis and comparison among them were provided, including results, the state-of-the-art, common errors, and possible points of improvement for future researchers.

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Cite this paper

@article{faria2023visual,
  title  = {Visual Question Answering: A Survey on Techniques and Common Trends in Recent Literature},
  author = {Ana Cláudia Akemi Matsuki de Faria and Felype de Castro Bastos and José Victor Nogueira Alves da Silva and Vitor Lopes Fabris and Valeska de Sousa Uchoa and Décio Gonçalves de Aguiar Neto and Claudio Filipi Goncalves dos Santos},
  year   = {2023},
  eprint = {2305.11033},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2305.11033v2}
}

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