Video Question

Video question answering (VideoQA) aims to enable computers to understand and respond to questions about video content, bridging the gap between visual and linguistic understanding. Current research focuses on improving model efficiency and accuracy by employing techniques like adaptive frame sampling, multi-agent systems, and leveraging large language models (LLMs) for reasoning and answer generation, often incorporating attention mechanisms and contrastive learning. This field is significant for advancing artificial intelligence's ability to interact with complex multimedia data, with potential applications ranging from assistive technologies for visually impaired individuals to more efficient video search and analysis.