VisionAidQA: Advancing Visual Question Answering for the Visually Impaired

This survey explores the advancements in Visual Question Answering (VQA) technology designed for visually impaired (VI) individuals. VQA systems integrate computer vision (CV) and natural language processing (NLP). It has the potential to improve VI people’s independence by translating visual information into understandable representations. Compared to other recent surveys, this survey not only focuses on the development of the VQA system but also demonstrates the challenges faced by VI people. This article provides an in-depth review of the state-of-the-art VQA systems, datasets, and methodologies, focusing on their application to assist VI users. We analyze the unique challenges faced by this demographic, such as the quality of images captured and the complexity of questions asked. The survey also highlights the specific needs of VI users and how existing VQA solutions address these needs. We discuss the role of multimodal transformers, prompt-based learning, and generative approaches in improving VQA performance. We discuss how it aligns with the Sustainable Development Goals (SDGs). Our findings emphasize the importance of developing customized VQA systems that meet the diverse requirements of VI individuals, leading the way for future research and innovation in this field. This comprehensive review aims to provide valuable insights and guidance for researchers and developers working on VQA technologies for VI people.