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README.md
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---
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license: other
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viewer: false
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task_categories:
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- text-generation
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language:
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- en
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tags:
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- language-modeling
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- casual-lm
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- llm
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pretty_name: Dolma
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size_categories:
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- n>1T
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extra_gated_prompt: "Access to this dataset is automatically granted upon accepting the [**AI2 ImpACT License - Medium Risk Artifacts (“MR Agreement”)**](https://allenai.org/licenses/impact-mr) and completing all fields below."
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extra_gated_fields:
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Your full name: text
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Organization or entity you are affiliated with: text
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State or country you are located in: text
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Contact email: text
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Please describe your intended use of the medium risk artifact(s): text
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I AGREE to the terms and conditions of the MR Agreement above: checkbox
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I AGREE to AI2’s use of my information for legal notices and administrative matters: checkbox
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I CERTIFY that the information I have provided is true and accurate: checkbox
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---
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# DIVOTrack: A Novel Dataset and Baseline Method for Cross-View Multi-Object Tracking in DIVerse Open Scenes
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The license agreement for data usage implies the citation of the paper above. Please notice that citing the dataset URL instead of the publications would not be compliant with this license agreement. You can read the LICENSE from [LICENSE](https://github.com/shengyuhao/DIVOTrack/blob/main/LICENSE.md).
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## <a id="con">Contact</a>
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If you have any concerns, please contact [shengyuhao@zju.edu.cn](shengyuhao@zju.edu.cn)
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# DIVOTrack: A Novel Dataset and Baseline Method for Cross-View Multi-Object Tracking in DIVerse Open Scenes
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The license agreement for data usage implies the citation of the paper above. Please notice that citing the dataset URL instead of the publications would not be compliant with this license agreement. You can read the LICENSE from [LICENSE](https://github.com/shengyuhao/DIVOTrack/blob/main/LICENSE.md).
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## <a id="con">Contact</a>
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If you have any concerns, please contact [shengyuhao@zju.edu.cn](shengyuhao@zju.edu.cn)
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