VideoLLM-online: Online Video Large Language Model for Streaming Video
Joya Chen, Zhaoyang Lv, Shiwei Wu, Kevin Qinghong Lin, Chenan Song, Difei Gao, Jia-Wei Liu, Ziteng Gao, Dongxing Mao, Mike Zheng Shou
Abstract
This is the Llama-3 upgraded version for CVPR camera-ready. responses in real-world video streams. With our LIVE framework, we built VideoLLM-online model upon Llama-2/Llama-3 and demonstrate its significant advantages in processing streaming videos. For instance, on average, our model can support streaming dialogue in a 5-minute video clip at over 10 FPS on an A100 GPU. Moreover, it also showcases state-of-the-art performance on public offline video benchmarks, such as recognition, captioning, and forecasting. The code, model, data, and demo have been made available at showlab.github.io/videollm-online.
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Install the CLIlune papers fulltext 0d71cbea-670a-4267-bd8f-8e2243840271Cited by top-tier papers83
- Video-R1: Reinforcing Video Reasoning in MLLMsKaituo Feng, Kaixiong Gong, Bohao Li, Zonghao Guo et al.NeurIPS 2025 · 528 citations
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- StreamForest: Efficient Online Video Understanding with Persistent Event MemoryXiangyu Zeng, Kefan Qiu, Qingyu Zhang, Xinhao Li et al.NeurIPS 2025 · 79 citations
- VideoLLM-MoD: Efficient Video-Language Streaming with Mixture-of-Depths Vision ComputationShiwei Wu, Joya Chen, Kevin Qinghong Lin, Qimeng Wang et al.NeurIPS 2024 · 78 citations
Builds on38
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- An Image is Worth 16x16 Words: Transformers for Image Recognition at ScaleAlexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn et al.ICLR 2021 · 21,477 citations
- Visual Instruction TuningHaotian Liu, Chunyuan Li, Qingyang Wu, Yong Jae LeeNeurIPS 2023 · 11,349 citations
- BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language ModelsJunnan Li, Dongxu Li, Silvio Savarese, Steven C. H. HoiICML 2023 · 7,873 citations
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