Video Language Modeling

Video language modeling aims to enable computers to understand and reason about the relationship between videos and accompanying text, facilitating tasks like video question answering and text-to-video retrieval. Current research focuses on developing efficient model architectures that effectively handle long videos, often employing techniques like temporal grounding, slot-based representations, and selective frame processing to reduce computational costs while maintaining accuracy. These advancements are significant because they improve the ability of machines to understand complex visual narratives, impacting fields such as video search, content summarization, and accessibility technologies.