In this episode, we discuss VideoLLM-online: Online Video Large Language Model for Streaming Video by Joya Chen, Zhaoyang Lv, Shiwei Wu, Kevin Qinghong Lin, Chenan Song, Difei Gao, Jia-Wei Liu, Ziteng Gao, Dongxing Mao, Mike Zheng Shou. The paper discusses the development of the Learning-In-Video-Stream (LIVE) framework, which improves large multimodal models' ability to handle real-time streaming video inputs. The framework includes a training objective for continuous input, data generation for streaming dialogue, and an optimized inference pipeline, leading to enhanced performance and speed. This innovation, demonstrated through the VideoLLM-online model built on Llama-2/Llama-3, shows significant improvements in handling streaming videos and achieves state-of-the-art performance in various video-related tasks.
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