Online Video

Online video research focuses on bridging the semantic gap between video content and textual or other modalities, enabling improved retrieval, analysis, and generation. Current efforts concentrate on developing multimodal models, often employing transformer architectures and leveraging large-scale datasets from sources like YouTube, to achieve tasks such as video-to-music generation, enhanced text-video retrieval, and automatic content labeling. These advancements have significant implications for applications ranging from personalized content recommendation and improved search functionality to enabling more sophisticated robotic manipulation and facilitating the understanding of animal communication through video analysis.