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We provide the models used in our data curation pipeline in [📚 Surg-3M: A Dataset and Foundation Model for Perception in Surgical Settings](https://arxiv.org/abs/2503.19740) to assist with constructing the Surg-3M dataset (for more details about the Surg-3M dataset and our
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SurgFM foundation model, please visit our github repository at [🤖 GitHub](https://github.com/visurg-ai/surg-3m)) .
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This Hugging Face repository includes video storyboard classification models, frame classification models, and non-surgical object detection models. The model loader file can be found at [model_loader.py](https://huggingface.co/visurg/Surg3M_curation_models/blob/main/model_loader.py)
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We provide the models used in our data curation pipeline in [📚 Surg-3M: A Dataset and Foundation Model for Perception in Surgical Settings](https://arxiv.org/abs/2503.19740) to assist with constructing the Surg-3M dataset (for more details about the Surg-3M dataset and our
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SurgFM foundation model, please visit our github repository at [🤖 GitHub](https://github.com/visurg-ai/surg-3m)) .
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If you use our dataset, model, or code in your research, please cite our paper:
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```
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@inproceedings{Che2025,
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author = {Chengan Che and Chao Wang and Tom Vercauteren and Sophia Tsoka and Luis C. Garcia-Peraza-Herrera},
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month = {3},
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journal = {arXiv preprint arXiv:2503.19740},
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title = {Surg-3M: A Dataset and Foundation Model for Perception in Surgical Settings},
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year = {2025}
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}
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```
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This Hugging Face repository includes video storyboard classification models, frame classification models, and non-surgical object detection models. The model loader file can be found at [model_loader.py](https://huggingface.co/visurg/Surg3M_curation_models/blob/main/model_loader.py)
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