DeltaStreamer: Towards Human-Like Agentic Streaming Video Understanding
We propose DeltaStreamer, a novel agentic framework for streaming video understanding inspired by how humans observe, remember, and investigate. Streaming video understanding requires a system to retain evidence before knowing which details future queries will need. Existing approaches often obscure event transitions and omit relevant details when compressing video history, and
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We propose DeltaStreamer, a novel agentic framework for streaming video understanding inspired by how humans observe, remember, and investigate. Streaming video understanding requires a system to retain evidence before knowing which details future queries will need. Existing approaches often obscure event transitions and omit relevant details when compressing video history, and
DeltaStreamer introduces an agentic approach to streaming video understanding, mimicking human cognitive processes for observation and recall. This is crucial for ML engineers working on real-time AI systems, as it addresses challenges in retaining relevant information from continuous data streams and responding to dynamic queries.