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README.md
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@@ -14,8 +14,7 @@ Model card for <a href="https://recognize-anything.github.io/">Recognize Anythin
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**Recognition and localization are two foundation computer vision tasks.**
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- **The Segment Anything Model (SAM)** excels in **localization capabilities**, while it falls short when it comes to **recognition tasks**.
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- **The Recognize Anything Model (RAM) and Tag2Text** exhibits **exceptional recognition abilities**, in terms of **both accuracy and scope**.
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| <b> Pull figure from recognize-anything official repo | Image source: https://recognize-anything.github.io/ </b>|
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}
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@article{huang2023tag2text,
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title={Tag2Text: Guiding Vision-Language Model via Image Tagging},
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author={Huang, Xinyu and Zhang, Youcai and Ma, Jinyu and Tian, Weiwei and Feng, Rui and Zhang, Yuejie and Li, Yaqian and Guo, Yandong and Zhang, Lei},
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journal={arXiv preprint arXiv:2303.05657},
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year={2023}
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}
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```
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**Recognition and localization are two foundation computer vision tasks.**
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- **The Segment Anything Model (SAM)** excels in **localization capabilities**, while it falls short when it comes to **recognition tasks**.
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- **The Recognize Anything Model (RAM) and Tag2Text** exhibits **exceptional recognition abilities**, in terms of **both accuracy and scope**.
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| <b> Pull figure from recognize-anything official repo | Image source: https://recognize-anything.github.io/ </b>|
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}
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@article{huang2023tag2text,
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title={Tag2Text: Guiding Vision-Language Model via Image Tagging},
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author={Huang, Xinyu and Zhang, Youcai and Ma, Jinyu and Tian, Weiwei and Feng, Rui and Zhang, Yuejie and Li, Yaqian and Guo, Yandong and Zhang, Lei},
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journal={arXiv preprint arXiv:2303.05657},
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year={2023}
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}
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```
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