Long-Form Video Understanding

This application area focuses on systems that can deeply comprehend long-form video content such as lectures, movies, series episodes, webinars, and live streams. Unlike traditional video analytics that operate on short clips or isolated frames, long-form video understanding tracks narratives, procedures, entities, and fine-grained events over extended durations, often spanning tens of minutes to hours. It includes capabilities like question answering over a full lecture, following multi-scene storylines, recognizing evolving character relationships, and step-by-step interpretation of procedural or instructional videos. This matters because much of the world’s high-value media and educational content is long-form, and current models are not reliably evaluated or optimized for it. Benchmarks like Video-MMLU and MLVU, along with memory-efficient streaming video language models, provide standardized ways to measure comprehension, identify gaps, and enable real-time understanding on practical hardware. For media companies, streaming platforms, and education providers, this unlocks richer search, smarter recommendations, granular content analytics, and new interactive experiences built on robust, end-to-end understanding of complex video.