Video Search

Video search aims to efficiently retrieve relevant video clips based on textual or visual queries, a task complicated by the multimodal nature of video data. Current research focuses on improving cross-modal embedding techniques, often employing transformer-based architectures and generative models to better align textual queries with visual and audio features, addressing issues like the "modality gap" and vocabulary limitations. These advancements are crucial for enhancing the performance of video search engines and enabling more sophisticated applications like temporal grounding and interactive video retrieval, impacting fields ranging from advertising to archival research.