AhmedSSabir
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# Visual semantic with BERT-CNN
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This model can be used to assign an object-to-caption relatedness score, which is valuable for
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(1) caption diverse re-ranking, and (2) generate soft labels for caption filtering when scraping
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For the [dataset](https://huggingface.co/datasets/AhmedSSabir/Textual-Image-Caption-Dataset)
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# Visual semantic with BERT-CNN
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This model can be used to assign an object-to-caption relatedness score, which is valuable for
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(1) caption diverse re-ranking, and (2) generate soft labels for caption filtering when scraping text-to-captions from the internet.
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The model is trained with a strict filter of 0.4 similarity distance thresholds between the object and its related caption.
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For a quick start please have a look at this [colab](https://colab.research.google.com/drive/1N0JVa6y8FKGLLSpiG7hd_W75UYhHRe2j?usp=sharing)
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For the [dataset](https://huggingface.co/datasets/AhmedSSabir/Textual-Image-Caption-Dataset)
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