Video Question Answering: A survey of the state-of-the-art

Abstract

Video Question Answering (VideoQA) emerges as a prominent trend in the domain of Artificial Intelligence, Computer Vision, and Natural Language Processing. It involves developing systems capable of understanding, analyzing, and responding to questions about the content of videos. The Proposed survey presents an in-depth overview of the current landscape of Question Answering, shedding light on the challenges, methodologies, datasets, and innovative approaches in the domain. The key components of the Video Question Answering (VideoQA) framework include video feature extraction, question processing, reasoning, and response generation. It underscores the importance of datasets in shaping VideoQA research and the diversity of question types, from factual inquiries to spatial and temporal reasoning. The survey highlights the ongoing research directions and future prospects for VideoQA. Finally, the proposed survey gives a road map for future explorations at the intersection of multiple disciplines, emphasizing the ultimate objective of pushing the boundaries of knowledge and innovation.