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  "access_rights": "",
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  "author": "Hongda Liu",
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  "author": "Hongda Liu",
            
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  "author_email": "",
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  "author_email": "",
            
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  "citation": [],
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  "citation": [],
            
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  "creator_user_id": "17755db4-395a-4b3b-ac09-e8e3484ca700",
            
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  "defined_in": "https://doi.org/10.48550/arXiv.2308.14024",
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  "defined_in": "https://doi.org/10.48550/arXiv.2308.14024",
            
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  "doi": "10.57702/eibgp0mr",
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  "doi": "10.57702/eibgp0mr",
            
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  "doi_date_published": null,
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  "doi_date_published": "2024-12-16",
            
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  "doi_publisher": "TIB",
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  "doi_publisher": "TIB",
            
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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": "Yunlong Wang",
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      "extra_author": "Yunlong Wang",
            
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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": "Min Ren",
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      "extra_author": "Min Ren",
            
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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": "Junxing Hu",
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      "extra_author": "Junxing Hu",
            
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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": "Zhengquan Luo",
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      "extra_author": "Zhengquan Luo",
            
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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": "Guangqi Hou",
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      "extra_author": "Guangqi Hou",
            
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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": "Zhenan Sun",
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      "extra_author": "Zhenan Sun",
            
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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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      "description": "",
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      "description": "",
            
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      "display_name": "Action Recognition",
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      "display_name": "Action Recognition",
            
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      "name": "action-recognition",
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      "name": "action-recognition",
            
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      "title": "Action Recognition"
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      "title": "Action Recognition"
            
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      "description": "",
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      "description": "",
            
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      "display_name": "Long-tailed Action Recognition",
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      "display_name": "Long-tailed Action Recognition",
            
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      "name": "long-tailed-action-recognition",
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      "name": "long-tailed-action-recognition",
            
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      "title": "Long-tailed Action Recognition"
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      "title": "Long-tailed Action Recognition"
            
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    },
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      "description": "",
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      "description": "",
            
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      "display_name": "Skeleton-based Action Recognition",
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      "display_name": "Skeleton-based Action Recognition",
            
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      "name": "skeleton-based-action-recognition",
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      "name": "skeleton-based-action-recognition",
            
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      "title": "Skeleton-based Action Recognition"
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      "title": "Skeleton-based Action Recognition"
            
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    }
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  "landing_page": "https://github.com/firework8/BRL",
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  "landing_page": "https://github.com/firework8/BRL",
            
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  "license_title": null,
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  "metadata_created": "2024-12-16T20:37:13.716715",
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  "metadata_modified": "2024-12-16T20:37:14.089661",
            
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  "name": 
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  "name": 
            
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sentation-learning-for-long-tailed-skeleton-based-action-recognition",
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sentation-learning-for-long-tailed-skeleton-based-action-recognition",
            
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  "notes": "Skeleton-based action recognition has recently made 
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  "notes": "Skeleton-based action recognition has recently made 
            
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significant progress. However, data imbalance is still a great 
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significant progress. However, data imbalance is still a great 
            
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challenge in real-world scenarios. The performance of current action 
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challenge in real-world scenarios. The performance of current action 
            
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recognition algorithms declines sharply when training data suffers 
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recognition algorithms declines sharply when training data suffers 
            
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from heavy class imbalance. The imbalanced data actually degrades the 
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from heavy class imbalance. The imbalanced data actually degrades the 
            
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representations learned by these methods and becomes the bottleneck 
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representations learned by these methods and becomes the bottleneck 
            
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for action recognition. How to learn unbiased representations from 
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for action recognition. How to learn unbiased representations from 
            
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imbalanced action data is the key to long-tailed action recognition.",
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imbalanced action data is the key to long-tailed action recognition.",
            
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      "name": "long-tailed action recognition",
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      "name": "long-tailed action recognition",
            
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      "display_name": "skeleton-based action recognition",
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      "display_name": "skeleton-based action recognition",
            
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      "id": "584d703d-bede-49fb-a146-ecadde39fe8a",
            
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      "name": "skeleton-based action recognition",
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      "name": "skeleton-based action recognition",
            
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  "title": "Balanced Representation Learning for Long-tailed 
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  "title": "Balanced Representation Learning for Long-tailed 
            
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Skeleton-based Action Recognition",
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Skeleton-based Action Recognition",
            
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}
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}