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  "access_rights": "",
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  "access_rights": "",
            
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  "author": "Bo Li",
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  "author": "Bo Li",
            
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  "author_email": "",
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  "author_email": "",
            
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  "citation": [],
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  "defined_in": "https://doi.org/10.48550/arXiv.1807.02842",
            
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  "doi": "10.57702/73byovpm",
            
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  "doi_date_published": null,
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  "doi_date_published": "2024-12-16",
            
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  "extra_authors": [
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  "extra_authors": [
            
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    {
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    {
            
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      "extra_author": "Tianfu Wu",
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      "extra_author": "Tianfu Wu",
            
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      "orcid": ""
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      "orcid": ""
            
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    },
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    {
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    {
            
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      "extra_author": "Lun Zhang",
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      "extra_author": "Lun Zhang",
            
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      "orcid": ""
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      "orcid": ""
            
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    },
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    },
            
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    {
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    {
            
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      "extra_author": "Rufeng Chu",
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      "extra_author": "Rufeng Chu",
            
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      "orcid": ""
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      "orcid": ""
            
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    }
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  ],
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      "description": "",
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      "description": "",
            
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      "display_name": "Object Detection",
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      "display_name": "Object Detection",
            
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      "name": "object-detection",
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      "name": "object-detection",
            
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      "title": "Object Detection"
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      "title": "Object Detection"
            
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  "name": "auto-context-r-cnn",
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  "name": "auto-context-r-cnn",
            
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  "notes": "Region-based convolutional neural networks (R-CNN) have 
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  "notes": "Region-based convolutional neural networks (R-CNN) have 
            
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largely dominated object detection. Operators de\ufb01ned on RoIs 
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largely dominated object detection. Operators de\ufb01ned on RoIs 
            
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(Re-gion of Interests) play an important role in R-CNNs such as 
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(Re-gion of Interests) play an important role in R-CNNs such as 
            
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RoIPooling and RoIAlign. They all only utilize information inside RoIs 
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RoIPooling and RoIAlign. They all only utilize information inside RoIs 
            
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for RoI prediction, even with their recent deformable extensions.",
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for RoI prediction, even with their recent deformable extensions.",
            
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      "display_name": "object detection",
            
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      "id": "607283c7-9e12-4167-9101-7f8078fb6537",
            
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      "name": "object detection",
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      "name": "object detection",
            
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      "state": "active",
            
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    },
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    {
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    {
            
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      "display_name": "region-based convolutional neural networks",
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      "display_name": "region-based convolutional neural networks",
            
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      "id": "3f11ec59-0ade-4a1b-8a80-a261db98a6ca",
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      "id": "3f11ec59-0ade-4a1b-8a80-a261db98a6ca",
            
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      "name": "region-based convolutional neural networks",
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      "name": "region-based convolutional neural networks",
            
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      "vocabulary_id": null
            
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    }
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  ],
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  ],
            
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  "title": "Auto-Context R-CNN",
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  "title": "Auto-Context R-CNN",
            
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  "type": "dataset",
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  "type": "dataset",
            
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  "version": ""
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  "version": ""
            
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}
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}