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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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# 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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## Model details |
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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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**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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## 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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@article{wang2024grounded, |
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title={Grounded-VideoLLM: Sharpening Fine-grained Temporal Grounding in Video Large Language Models}, |
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author={Wang, Haibo and Xu, Zhiyang and Cheng, Yu and Diao, Shizhe and Zhou, Yufan and Cao, Yixin and Wang, Qifan and Ge, Weifeng and Huang, Lifu}, |
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journal={arXiv preprint arXiv:2410.03290}, |
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year={2024} |
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} |
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``` |
