This dataset card aims to provide a comprehensive overview of the StreamingChat model. For details, see our Project, Paper, Dataset and GitHub repository.

StreamingChat is a streaming video understanding model built upon InternVideo2.5. It utilizes Streaming video dialogue data, including temporal dialogue paths from the SVBench training set. The model is fine-tuned using a static resolution strategy, enabling it to process several minutes of video at a rate of 1 FPS. Images are interleaved with language tokens, with each image comprising 16 tokens. This model aims to catalyze progress in streaming video understanding.

Download the StreamingChat model from Hugging Face:

Install Python dependencies:

Run the inference script directly：

If you find our data useful, please consider citing our work!

@article{yang2025svbench,
  title={SVBench: A Benchmark with Temporal Multi-Turn Dialogues for Streaming Video Understanding},
  author={Yang, Zhenyu and Hu, Yuhang and Du, Zemin and Xue, Dizhan and Qian, Shengsheng and Wu, Jiahong and Yang, Fan and Dong, Weiming and Xu, Changsheng},
  journal={arXiv preprint arXiv:2502.10810},
  year={2025}
}