New framework enables VLMs to process live video streams

Researchers have developed a new framework called Streaming Harness to enable Vision-Language Models (VLMs) to process unbounded video streams in real-time. This system enhances VLMs with proactive interaction, long-term memory retention up to 12 hours, and sub-second processing latency. To support this advancement, they also introduced a new streaming dataset, Streaming-Train-248K, and a benchmark, Streaming-Eval, to drive further progress in deployable streaming intelligence. AI

IMPACT Enables real-time analysis of live video feeds for applications like assistants and robotics, moving beyond offline video understanding.

RANK_REASON The cluster contains an academic paper detailing a new system, dataset, and benchmark for processing streaming video with VLMs. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

• Streaming-Eval
• Streaming Harness
• Streaming-Train-248K
• Vision-Language Models

• paper
• product
• infra

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