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
摘要
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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引用它的顶会 Paper83
- Video-R1: Reinforcing Video Reasoning in MLLMsKaituo Feng, Kaixiong Gong, Bohao Li, Zonghao Guo 等NeurIPS 2025 · 被引用 528 次
- Cambrian-S: Towards Spatial Supersensing in VideoShusheng Yang, Jihan Yang, Pinzhi Huang, Ellis Brown 等ICLR 2026 · 被引用 139 次
- StreamingVLM: Real-Time Understanding for Infinite Video StreamsRuyi Xu, Guangxuan Xiao, Yukang Chen, Liuning He 等ICLR 2026 · 被引用 95 次
- StreamForest: Efficient Online Video Understanding with Persistent Event MemoryXiangyu Zeng, Kefan Qiu, Qingyu Zhang, Xinhao Li 等NeurIPS 2025 · 被引用 79 次
- VideoLLM-MoD: Efficient Video-Language Streaming with Mixture-of-Depths Vision ComputationShiwei Wu, Joya Chen, Kevin Qinghong Lin, Qimeng Wang 等NeurIPS 2024 · 被引用 78 次
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