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  "citation": [
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  "citation": [
            
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    "https://doi.org/10.48550/arXiv.2111.14341",
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    "https://doi.org/10.48550/arXiv.2111.14341",
            
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    "https://doi.org/10.48550/arXiv.1911.12451"
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    "https://doi.org/10.48550/arXiv.1911.12451"
            
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  "doi_date_published": null,
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      "extra_author": "S. A. Eslami",
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      "extra_author": "S. A. Eslami",
            
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    },
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      "extra_author": "L. Van Gool",
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      "extra_author": "L. Van Gool",
            
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      "extra_author": "C. K. Williams",
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    },
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      "extra_author": "J. Winn",
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      "extra_author": "J. Winn",
            
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      "orcid": ""
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    },
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      "extra_author": "A. Zisserman",
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      "extra_author": "A. Zisserman",
            
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      "title": "Object Detection"
            
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      "name": "semantic-segmentation",
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      "name": "semantic-segmentation",
            
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  "name": "pascal-visual-object-classes-challenge",
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  "name": "pascal-visual-object-classes-challenge",
            
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  "notes": "The PASCAL Visual Object Classes Challenge (VOC) is a 
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  "notes": "The PASCAL Visual Object Classes Challenge (VOC) is a 
            
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benchmark dataset for object detection and semantic segmentation.",
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benchmark dataset for object detection and semantic segmentation.",
            
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}