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--- |
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license: agpl-3.0 |
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datasets: |
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- rafaelpadilla/coco2017 |
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- nateraw/kitti |
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- Chris1/cityscapes |
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- dgural/bdd100k |
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metrics: |
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- precision |
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- f1 |
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- recall |
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pipeline_tag: object-detection |
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--- |
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# Model Card for Model ID |
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<!-- Provide a quick summary of what the model is/does. --> |
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Butter is a novel 2D object detection framework designed to enhance hierarchical feature representations for improved detection robustness. |
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## Model Details |
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### Model Description |
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<!-- Provide a longer summary of what this model is. --> |
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- **Developed by:** [Xiaojian Lin et al.] |
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- **Funded by:** [National Natural Science Foundation of China] |
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- **Model type:** [Object Detection] |
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- **License:** [AGPL-3.0 license] |
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### Model Sources [optional] |
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<!-- Provide the basic links for the model. --> |
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- **Repository:** [https://github.com/Aveiro-Lin/Butter] |
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- **Paper:** [https://www.arxiv.org/pdf/2507.13373] |
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## Uses |
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The training and inference details, as well as the environment configuration, can be found in our GitHub repository, where a comprehensive description is provided. The model’s performance metrics and training details are thoroughly described in the paper we provide. |
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