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+ ---
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+ license: mit
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+ language:
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+ - en
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+ ---
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+
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+ # Grounded-VideoLLM Model Card
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+ Grounded-VideoLLM is a Video-LLM adept at fine-grained temporal grounding, which not only excels in grounding tasks such as temporal sentence grounding, dense video captioning, and grounded VideoQA, but also shows great potential as a versatile video assistant for general video understanding.
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+
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+ ## Model details
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+
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+ **Model date:**
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+ Grounded-VideoLLM-Phi3.5-Vision-Instruct was trained in Oct. 2024.
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+
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+ **Paper or resources for more information:**
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+ [Paper](https://arxiv.org/abs/2410.03290), [Code](https://github.com/WHB139426/Grounded-Video-LLM)
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+
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+ ## Citation
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+ If you find our project useful, hope you can star our repo and cite our paper as follows:
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+
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+ ```
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+ @misc{wang2024groundedvideollm,
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+ title={Grounded-VideoLLM: Sharpening Fine-grained Temporal Grounding in Video Large Language Models},
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+ author={Haibo Wang and Zhiyang Xu and Yu Cheng and Shizhe Diao and Yufan Zhou and Yixin Cao and Qifan Wang and Weifeng Ge and Lifu Huang},
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+ year={2024},
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+ eprint={2410.03290},
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+ archivePrefix={arXiv},
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+ primaryClass={cs.CV}
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+ }
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+ ```