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

Source: [Visual Question Answering: A Survey on Techniques and Common Trends in Recent Literature](<https://www.sota2.com/research/paper/68fa6f8f1e209131cea463ed>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-26T01:22:26.639Z

Authors: Ana Cl\\'audia Akemi Matsuki de Faria, Felype de Castro Bastos, Jos\\'e Victor Nogueira Alves da Silva, Vitor Lopes Fabris, Valeska de Sousa Uchoa, D\\'ecio Gon\\c{c}alves de Aguiar Neto, Claudio Filipi Goncalves dos Santos

Published: 2023-05-18T15:20:11.000Z

## 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.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2305.11033>)

[PDF](<https://arxiv.org/pdf/2305.11033.pdf>)